Techniques for increasing the capacity of wireless broadband networks: UK, 2012-2030

Techniques for increasing the capacity of wireless broadband networks: UK, 2012-2030 Produced by Real Wireless on behalf of Ofcom Issued to: Ofcom Real Wireless Ltd PO Box 2218 Pulborough t +44 2071178514 West Sussex f +44 8082800142 RH20 4XB e info@realwireless.biz United Kingdom www.realwireless.biz

Version Control Item Source Client Report title Sub title Description Real Wireless Ofcom Issue date April 2012 Document number Document status Comments Techniques for increasing the capacity of wireless broadband networks: UK, 2012-2030 Produced by Real Wireless on behalf of Ofcom Version Date Comment 1.15 26/03/2012 Issued to Ofcom for publication 1.16 16/04/2012 Minor amendment (2012 site numbers scenarios 22-39) to table 1-1

About Real Wireless Real Wireless is a leading independent wireless consultancy, based in the U.K. and working internationally for enterprises, vendors, operators and regulators indeed any organization which is serious about getting the best from wireless to the benefit of their business. We seek to demystify wireless and help our customers get the best from it, by understanding their business needs and using our deep knowledge of wireless to create an effective wireless strategy, implementation plan and management process. We are experts in radio propagation, international spectrum regulation, wireless infrastructures, and much more besides. We have experience working at senior levels in vendors, operators, regulators and academia. We have specific experience in LTE, UMTS, HSPA, Wi-Fi, WiMAX, DAB, DTT, GSM, TETRA and many more. For details contact us at: info@realwireless.biz Tap into our news and views at: realwireless.wordpress.com Stay in touch via our tweets at twitter.com/real_wireless Copyright 2012 Real Wireless Limited. All rights reserved. Registered in England & Wales No. 6016945

Executive summary This project was conducted by Real Wireless on behalf of Ofcom in order to determine the role which existing and additional spectrum, notably a potential 700 MHz band, might play in meeting growing demand for wireless broadband capacity over the next 10 to 20 years. The role of additional spectrum is considered against the background of a wide range of other capacity-enhancing techniques including LTE-Advanced and small cells which the wireless industry is developing and which are expected to emerge over the study period. In particular, we determined the extent to which the addition of 700 MHz and other harmonised spectrum bands affect the cost of delivering wireless broadband in the UK using standardized mobile technologies over the period from 2012 to 2030 given: Existing mobile spectrum plus 800 MHz and 2600 MHz as a baseline in 2012 Expected growth in the (spectrum and productive) efficiency of mobile technologies and topologies over the period A range of possible scenarios for the growth in quantity and nature of UK demand over the period. We adopted a modelling framework which explicitly models the cost of efficiently meeting wireless demand arising from the deployment of varying timing and quantity of suitable spectrum. We examine the whole of the UK market and costs incurred by society as a whole, rather than examining the view of any individual operator. Three study regions were chosen to represent urban, suburban and rural environments, between which the capacity/cost tradeoffs are significantly different, but which together additionally comprise a significant portion (around 6%) of the overall UK demand. We have considered the potential merits of an extensive range of potential capacityenhancing techniques in spectrum, technology and topology dimensions, summarised in Table 0-1. For each technique we have assigned, based on our research, a range of views as to the opportunity for it to increase capacity, as well as the cost of deploying the technique given an existing network, considering both capital and operational expenditure requirements over the whole study period. Our modelling uses this information to determine the combination of these technologies which meets the demand on a cost efficient basis given our estimates of the costs of deploying each technology, accounting for factors such as the increasing cost of acquiring suitable sites as the density rises, the relative cost of upgrading existing sites versus building new ones, the costs of replacing and upgrading base station equipment over time, etc. 4

Table 0-1: Capacity-enhancing techniques: opportunities and challenges Spectrum / Technology / Topology Capacityenhancing technique Opportunities Challenges Spectrum Technology Public sector spectrum bands 700 MHz band White space UHF spectrum MIMO (multiple antenna technology) Enhanced modulation and coding efficiency Large quantities of high-frequency spectrum for capacity Useful physical properties for coverage and spectrum efficiency Wider bandwidth than currently available in sub 1GHz bands Increases supply of sub-1ghz spectrum Significant spectrum efficiency gains Potential to increase spectral efficiency from existing sites with little hardware change No identified spectrum below 1 GHz Relies on international harmonisation and associated standards support Relies on sufficient adoption to drive take-up by manufacturers in mass-market mobile devices Proliferation of bands increases device cost and may decrease performance International adoption in the European configuration for this band Uncertain availability and long timescale Alternative uses including broadcasting Proliferation of bands increases device cost and may decrease performance Constraints on protecting TV use limits opportunity to relatively short range devices Variability of supply by geographical location and over time Questionable harmonised support in mass market devices Impact limited at cell edge due to low signal quality Impact variable depending on spatial channel conditions Requires multiple antennas at base stations and mobile devices with impact on space, power consumption and practicality Large proportion of devices required to impact system capacity significantly Potential for further gains limited due to proximity of current technology to Shannon limit Gains typically require good signal strength and quality, so limited by interference when demand is high 5

Topology Coordinated Multipoint and Cloud RAN Carrier Aggregation Offload via femtocells Offload via Wi-Fi Extensive use of outdoor Joint processing of signals at different sites can transform interference into useful signals Permits centralised capacity to be shared across dispersed geographical and temporal demand peaks Allows devices to access multiple increments of spectrum, potentially in multiple bands Facilitates refarming of existing spectrum Increases effective device bandwidth which can extend coverage Suitable for offloading indoor traffic which constitutes a large proportion of current and expected total demand Potentially closely targeted to locations with specific need Licenced spectrum to manage quality of service Improved coverage and user experience as well as capacity Supported by all mobile devices Suitable for offloading indoor traffic Widely deployed population of existing access points Growing support in mobile devices and for carrier-managed mobile experience Cost-effective supply of capacity to localised hotspots Requires extensive, fast, low latency interconnect between sites (typically fibre) Centralising capacity may increase cost-effectiveness but does not directly impact maximum capacity density Does not directly increase available supply of capacity, just access to the available spectrum Support in devices may be limited to specific band combinations and RF performance may be less than a single band solution Interference and mobility coordination with wide network Availability of suitable backhaul To maintain or increase the proportion of offload, substantial increase over time in the capacity per femtocell will be required May be difficult to target on the most needy locations, reducing cost-effectiveness Support for seamless call and encryption mobility Battery life concerns Users may disable capability Congestion of licence-exempt spectrum Availability of suitable backhaul To maintain proportion of offload, substantial increase over time in access point capacity will be required May be difficult to target on the most needy locations, reducing cost-effectiveness Difficult to predict and locate the hotspots with precision and they may change location 6

small cells Extension of coverage to small settlements in rural areas Additional macrocells Capacity delivered over wide area significantly over time Challenge in acquiring the right sites and providing power and backhaul Potential need for site sharing amongst operators to avoid excessive proliferation Lack of suitable sites Increased necessity for infrastructure sharing amongst operators Impact of 700 MHz availability Following modelling of our mid-range demand and capacity (= spectrum, offload & spectrum efficiency) scenarios, Figure 0-1 illustrates how the number of macrocell sites rises for the suburban study area, while Figure 0-2 shows the impact on the number of small cell sites. In the absence of 700 MHz, a spectrum crunch is encountered between 2022 and 2025, where existing sites have been upgraded to the full extent of the available technology and spectrum, and the only option for meeting further demand growth is to rapidly increase the number of both macrocell sites and small cells. The availability of 700 MHz in 2026 would minimise increases in sites beyond that point but too late to avoid the large site-build programme which is indicated. By contrast, bringing 700 MHz availability forward to 2020 reduces the scale of the rapid build-out programme and delays it until towards the end of the study period. We also examine the impact of 700 MHz availability on incremental network costs. Network costs are presented throughout this report on the basis of present values in 2012 with social discount rates. Present values are calculated on the basis of incremental expenditure from 2012 to 2040, with the size of the network remaining constant beyond the study period (i.e. from 2030 to 2040). Given the uncertainties implicit in assigning costs to future network roll-out over the long study period, these costs should be treated as illustrative and as a basis for comparison between options, rather than as representing future costs on an absolute basis. Note also that this summary provides only the network costs, which do not include the costs of providing and operating indoor offload equipment. A similar impact is seen when examining the difference in network costs according to the availability of 700 MHz and indeed in the other study areas in Figure 0-3. The relative savings of the presence of 700 MHz in terms of both network costs and cell sites are summarised in Figure 0-4. Note that these savings are substantially greater than the 5%-9% of relevant spectrum bands which 700 MHz spectrum represents, indicating how the particular physical properties of lower frequency spectrum can provide a benefit disproportionate to its quantity. Timing of 700 MHz availability relative to the spectrum crunch is critical: for example, network costs are reduced by 41% in the suburban area given 700 MHz in 2020, but by 21% with 700 MHz in 2026. We assumed a reasonable depth and consistency of indoor coverage consistent with other Ofcom studies. A greater depth and/or consistency could further increase the relative impact of low frequency spectrum such as 700 MHz. Similarly, we have assumed that the 700 MHz is available to support the whole market: if 700 MHz were made available to an individual operator who would not otherwise have such spectrum, the impact on that operator could be greater still. 7

Number of macro sites, relative to 2012 x1.10 x1.09 x1.08 x1.07 x1.06 x1.05 x1.04 x1.03 x1.02 x1.01 Sub Lon, Never Sub Lon, 2026 Sub Lon, 2020 x1.00 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 0-1: Growth in macrocell sites for suburban area according to availability of 700 MHz (mid demand and capacity scenarios) 180 Number of small cells 160 140 120 100 80 60 40 Sub Lon, Never Sub Lon, 2026 Sub Lon, 2020 20 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Figure 0-2: Growth in outdoor small cell sites for suburban area according to availability of 700 MHz (mid demand and mid capacity scenarios) 2022 2023 2024 2025 2026 2027 2028 2029 2030 8

Network costs to 2040 ( m) 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 8.6 6.2 6.8 14.2 8.4 11.1 12.3 10.5 11.0 - Never 2020 2026 Never 2020 2026 Never 2020 2026 Urban Suburban Rural Figure 0-3: Impact of 700 MHz timing on network cost (mid demand and mid capacity scenarios). Costs should be treated as illustrative and relative rather than absolute Saving (relative to no 700 MHz) 60% 50% 40% 30% 20% 10% 21% 19% 42% 31% 28% 28% 21% 35% 52% 41% 55% 57% Network Cost saving (to 2040) New site saving (macro) New site saving (total) 22% 22% 21% 18% 15% 11% 0% 2026 2020 2026 2020 2026 2020 Urban Suburban Rural Figure 0-4: Relative savings in network costs (to 2040) and new cell sites (by 2030) arising from the availability of 700 MHz in 2020 or 2026 (mid demand and mid capacity scenarios) Impact of offload assumptions on utility of 700 MHz One of the assumptions in our modelling is that a substantial fraction of demand which occurs in indoor locations can be offloaded via Wi-Fi and femtocells. We assume that offload in suburban and urban areas is currently around 40% of total traffic and will grow over the study period to 50% in our mid scenario (and a somewhat lower level in rural areas). Such an apparently modest growth in the fraction offloaded actually represents a very substantial growth in the volume of traffic, given the underlying total demand growth. It could be, therefore, that in practice the volume of offload is limited, or that practical factors such as backhaul capability and the need to target devices for the most needy locations limit the level 9

of offload relative to our assumptions. Figure 0-5 shows that varying the potential level of offload (to 45 % by 2030 in our low scenario, and 60 % in our high scenario) varies the network costs, with a higher cost to meet the same total demand to compensate for lower offload. Figure 0-6 shows that lower offload also increases the number of cell sites needed. In all of our study environments, however, the network costs with the lowest level of offload in the presence of 700 MHz (in 2020) are still lower than those incurred with the highest level of offload in the absence of 700 MHz. Thus the presence of 700 MHz can reduce the necessary level of offload (and further reduce the associated costs of establishing and running the offload devices, which are not included in this comparison) or indeed can make a given level of offload more effective overall. Network costs to 2040 ( m) 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0-7.0 6.2 Lo Med 4.7 Hi 9.4 8.6 7.3 Lo Med Hi 10.3 Lo 8.4 Med 6.3 Hi 15.6 14.2 Lo Med 12.4 12.3 10.8 10.9 11.4 10.5 9.7 Hi Lo Med Hi Lo Med 2020 Never 2020 Never 2020 Never Urban Urban Suburban Suburban Rural Rural Hi Figure 0-5: Impact of varying offload assumptions on network costs (to 2040), with and without availability of 700 MHz in 2020 (mid demand and mid capacity scenarios). Costs should be treated as illustrative and relative rather than absolute 10

700 No. of cell sites 600 500 400 300 200 100 0 453447 423 485481485 118 75 45 179 162132 108106100114111103 Lo Med Hi Lo Med Hi 48 25 25 40 29 24 237236230 252247 236 189192187 199202199 Lo Med small cells in '30 macros in '30 Hi Lo Med Hi Lo Med Hi Lo Med Hi 2020 Never 2020 Never 2020 Never Urban Urban Suburban Suburban Rural Rural Figure 0-6: Impact of varying offload assumptions on cell sites (in 2030), with and without availability of 700 MHz in 2020 (mid demand and mid capacity scenarios) Impact of public sector spectrum availability A substantial portion of the spectrum growth represented in our mid-case spectrum scenario is from public sector spectrum holdings, representing some 22% of the total relevant spectrum by 2030. In Figure 0-8 we show the impact on the network costs of that spectrum becoming available more rapidly, reaching 24% of relevant spectrum ( hi ) or at a slower rate ( late pub. sect ), where it represents only 11% of spectrum in 2030. The corresponding impact on cell sites is shown in Figure 0-7. It is clear that public sector spectrum forms a significant element of overall mobile capacity and its availability and usefulness (including the impact of harmonisation) can substantially impact on the scale of network build-out and the costs of meeting future demand, especially in urban and suburban areas where demand density is highest. 11

800 700 No. of cell sites 600 500 400 300 200 100 0 611 447 400 132 106 98 late pub. sect. 158 292 Mid Hi late pub. sect. 75 59 37 25 25 236 231 192 192 188 Mid Hi late pub. sect. Small cells 2030 Macrocells 2030 Mid Urban Suburban Rural Hi Figure 0-7: Impact of varying the rate and quantity of public sector spectrum on cell sites (in 2030), with and without availability of (mid demand and mid capacity scenarios, 700 MHz in 2020). 25 21.7 22.5 Network costs to 2040 ( m) 20 15 10 5 6.2 3.2 8.4 6.8 10.8 10.5 9.7 0 late pub. sect. Mid Hi late pub. sect. Mid Hi late pub. sect. Mid Urban Suburban Rural Hi Figure 0-8: Impact of varying the rate and quantity of public sector spectrum on network costs (to 2040), with and without availability of (mid demand and mid capacity scenarios, 700 MHz in 2020). Costs should be treated as illustrative and relative rather than absolute.. 12

Summary Given the long time period at issue here, there are very substantial uncertainties in the size and timing of both the demand for wireless services and the supply of capacity. This has been demonstrated by analysing the key sensitivities such as the timing of 700 MHz, the quantity and availability of spectrum and the level of offloaded demand. However there are various other assumptions that could materially impact the impact of 700 MHz, as summarised in Table 0-1 and in more detail in our report. Nevertheless, our study indicates the plausible ranges of these factors given current knowledge in the UK situation and provides a means of establishing the critical factors to balance demand and the supply of capacity with regard to both the scale and the cost of the necessary networks and establishes a guide to policy makers and operators as the period passes. Our key findings are summarised in Table 0-2.Overall, our study indicates clearly that both lower frequency and higher frequency spectrum have a role to play in future mobile capacity and that additional spectrum acts in combination with other sources of capacity such as small cells, offload and technology enhancements, with each approach benefiting from the presence of the others, rather than as substitutes. 13

Table 0-2: Summary of key findings Issue Finding based on our analysis Commentary Demand trends Impact of technological innovation Spectrum growth Impact of 700 MHz Based on current trends and our analysis of devices and user mobility, mobile broadband is projected to grow between 23x and 297x over the period 2012-30, with 80x being our mid case scenario. While growth will be high over the period, there is potential for the growth rate to reduce in the latter stages of this period. The non-uniformity of traffic between users, locations and environments (indoors and outdoors) and times of day is a major driver of the required form of capacity enhancement. The evolution of enhanced technologies, including via LTE- Advanced and its evolutions could deliver spectrum efficiency growth to existing cell sites of between 3.3x and 10.1x between 2012 and 2030, with a mid case of 6.2x. We have analysed the associated costs and provided guidance on the relative merits of the available techniques. Beyond the award of 800 MHz and 2.6 GHz, there is scope for substantial additional availability of harmonised spectrum for wireless services, representing around 350 MHz of additional spectrum for downlink capacity. This could deliver a growth in available spectrum capacity for the downlink between 7x and 13x over the period considered. This is expected to deliver sufficient capacity for networks of approximately the current scale of macrocells out to around 2024 with our mid-case growth and capacity assumptions (which include significant growth in macrocell spectrum efficiency and the number of small cells deployed). A 700 MHz band would represent only 5 to 9% of the relevant spectrum at 2030, but yields greater benefits due to its distinctive physical properties. These produce a benefit in terms of reducing the number of additional These ranges are not forecasts, but an indication of a plausible range of outcomes. Given this wide range, there is a need to secure options notably spectrum options for enhancing capacity, while making firm decisions on those options flexibly as the actual demand emerges. The inclusion of additional antennas in both base stations and mobile devices is key to achieving the higher growth rates, as is the successful adoption of advanced interference mitigation techniques supported by close coordination and low-latency backhaul between base stations. Public sector spectrum release at frequencies above 2 GHz forms a major element of future spectrum capacity, and the rate at which it becomes available, harmonised, and included in mass-market data devices could vary the rate of overall spectrum availability significantly. Both the coverage and the spectrum efficiency properties of 700 MHz play a role in it delivering a greater benefit than the quantity available would suggest, including in its ability to deliver reliable indoor coverage from outdoor sites. 14

Issue Finding based on our analysis Commentary Impact of outdoor small cells Impact of indoor traffic offload sites by between 18% and 52% (depending on the area) for 700 MHz availability in 2026 in the mid scenario for demand and capacity. Network costs are also reduced by between 11% and 27%. Earlier release in 2020 could substantially increase these benefits to 21%-57% site reduction and 15% to 41% network cost reduction. If operators can overcome challenges associated with determining localised areas of high demand and acquiring suitable sites to address them, then small cells are expected to play a significant role across all the scenarios studied. Growth varies substantially by region, but for our mid scenarios outdoor small cells represent 12% (rural) to 81% (urban) of all outdoor cells with 700 MHz availability in 2026, and somewhat higher without it. Indoor offload devices, whether using Wi-Fi or femtocells approaches in licence-exempt or licenced spectrum, already offload substantial traffic (around 30-40%) from wireless networks and this use is expected to increase, perhaps to as high as 60% by 2030. However, the costs can be substantial compared with outdoor network costs when widely deployed and this could limit offload deployments to some extent. If so, network costs are increased to compensate. The availability of 700 MHz in 2020 was found to mitigate this risk, reducing network costs in our lowest offload scenario to below those of our high offload scenario in the absence of 700 MHz. The impact of 700 MHz varies substantially with geographical area, depending on the balance of coverage and capacity. Where coverage limitations dominate areas, there is a reduction in the rate at which new sites need to be built. Where capacity limitations dominate, 700 MHz delays the advent of the need to build additional sites, which can significantly affect the cost although the relative timing of the spectrum availability and the capacity crunch is critical. Outdoor small cells act to reduce the number of additional macrocell sites (and associated costs) which would otherwise be required in two ways: They act as a low cost means of providing coverage to locations where the number of individuals affected is relatively small, for example in rural areas. This also helps the macrocells to continue to deliver wide area coverage without becoming range limited due to capacity constraints. They deliver capacity to localised hotspots of demand, allowing the growing capacity of macrocells to meet the wide-area capacity needs. This applies to any area with a wide spatial variation of traffic needs, and we observe significant growth for this purpose across all our study areas. There are open questions concerning the enabling factors for offload quantities to keep up with the growth of demand, including availability of suitable backhaul, sufficiency of spectrum (whether licenced or licence-exempt) and the ability of offload devices to be targeted on the most effective locations. We recommend further study of these issues. However the uncertainties may be less when addressing some proportion of indoor demand from outdoor sites, in which case spectrum bands such as 700 MHz could yield an increased benefit. 15

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Contents 1. Introduction and summary... 20 1.1 Background... 20 1.2 The scope of our study and our approach... 20 1.3 Sources of capacity... 22 1.4 Our approach... 23 1.5 Wireless broadband demand in the UK... 25 1.6 Data offload scenarios... 28 1.7 UK spectrum scenarios... 30 1.8 Spectrum efficiency... 31 1.9 Site ranges... 33 1.10 Network costs... 34 1.11 High level comparison of demand and supply... 35 1.12 The utility of low frequency spectrum... 38 1.13 Cost-efficient capacity expansion detailed results... 40 1.13.1 Mid Demand, Mid Capacity Scenarios... 43 1.13.2 The action of 700 MHz in delaying a capacity crunch... 48 1.13.3 High Demand, Low Capacity Scenarios... 51 1.13.4 Low Demand, High Capacity Scenarios... 52 1.13.5 Offload sensitivity analysis... 52 1.13.6 Spectrum sensitivity analysis... 56 1.14 Overall findings... 61 2. Introduction... 64 2.1 Scope of Study... 64 2.2 Related Studies... 65 2.3 Report structure... 67 3. Methodology and assumptions... 68 3.1 Overview of Modelling Framework... 68 3.2 Input scenarios to address Ofcom s questions... 69 3.3 Study Areas for modelling... 71 3.3.1 Coverage area assumptions for rural Lincolnshire... 74 3.4 Traffic Demand Assumptions... 76 3.4.1 Scenarios reflecting uncertainties in future demand... 77 3.4.2 Mobile data traffic offload... 77 3.4.3 Overall UK traffic growth... 78 3.5 Spectrum... 79 3.5.1 Net bandwidth available in each band over time... 79 17

3.5.2 Consideration of white space spectrum... 80 3.6 Spectrum scenarios... 82 3.7 Site Ranges... 83 3.8 Site Spectral Efficiency... 86 3.8.1 Technology Evolution: 3G-4G and beyond... 86 3.8.2 Device mix... 86 3.8.3 Site Configurations... 87 3.8.4 Geotype, carrier frequencies and indoor/outdoor demand... 88 3.8.5 Scenarios... 88 3.9 Site Costs... 89 3.9.1 Outline of the costs estimated... 89 3.9.2 Modelling timeframe... 90 3.9.3 Cost inputs for the technical model... 90 3.9.4 We estimate the costs to society... 91 3.9.5 Main cost estimates... 91 4. Results and analysis... 92 4.1 Introduction... 92 4.1.1 Quantity of 700 MHz as a proportion of total available spectrum... 92 4.1.2 Site range advantage from sub 1 GHz spectrum... 93 4.1.3 Spectral efficiency advantage from Sub 1 GHz... 94 4.2 High level capacity analysis and the need for site densification... 94 4.3 Results from timing and availability of 700MHz... 100 4.3.1 Explanation of our cost terminology... 100 4.3.2 Cost results... 102 4.3.3 Summary of costs across scenarios and study areas... 104 4.3.4 Timing of 700 MHz mid case scenario... 105 4.4 Results from high demand cases... 110 4.5 Results from low demand cases... 114 4.6 Role of 700 MHz for capacity... 117 4.7 Results from sensitivity analyses... 118 4.8 Results from offload sensitivity... 120 4.9 Results from spectrum sensitivity... 124 5. Overall findings...130 5.1 Introduction... 130 5.2 The utilisation of 700 MHz delivers an overall cost saving... 130 5.3 Further work and other analyses... 141 5.3.1 Impact of the differences between demand assumptions... 141 5.3.2 Alternative offload assumptions... 141 18

5.3.3 Uncertainties in spectrum availability... 141 5.3.4 Assumptions on a single network... 142 5.3.5 Practicality and challenges for deploying small cells... 142 5.3.6 Assumptions on uniform distribution of demand... 142 5.3.7 Assumption on indoor/outdoor demand split... 142 19

1. Introduction and summary This document represents the final report of a project conducted by Real Wireless on behalf of Ofcom to determine the role which existing and additional spectrum, notably a potential 700 MHz band, might play in meeting growing demand for wireless broadband capacity over the next 10 to 20 years. The role of additional spectrum is considered against the background of a wide range of other capacity-enhancing techniques including LTE-Advanced and small cells which the wireless industry is developing and which are expected to emerge over the study period. This chapter provides a stand-alone overview of our study and its outcomes. Subsequent chapters describe the study in greater detail, supported by companion documents containing extensive supporting annexes. 1.1 Background Wireless broadband demand is increasing rapidly and this growth, notably from mobile devices, is widely expected to continue for at least the next five years. In order to maximise the social and economic benefits associated with this growth, considerable extra capacity will be needed in wireless networks. One source of this additional capacity is radio spectrum: as the UK communications regulator, Ofcom is responsible for ensuring efficient use of this spectrum to the benefit of UK citizens and consumers. The UK is embarking on a considerable programme of identifying and awarding spectrum for these purposes, including via the forthcoming auction of 800 MHz and 2.6 GHz and also via the UK government s commitment to release 500 MHz of spectrum below 5 GHz by 2020, primarily from public sector spectrum holdings. Beyond this, Ofcom s chief executive recently identified the potential that 700 MHz spectrum could be cleared to meet additional demand: If the 700MHz band is harmonised throughout Europe for mobile use in the next decade, the opportunity may exist to replan Digital Terrestrial Television so that we are able to maximise the overall value of sub 1GHz spectrum to society. [ i ] However, the timescale required to bring spectrum to market may extend over many years or even decades, while demand forecasts over just the next few years vary over a very wide range. So the quantity of spectrum required to meet the demand is difficult to forecast. Allocation of an excess of spectrum for wireless broadband risks losing benefits from other potential uses, while insufficient spectrum allocated to wireless broadband risks the loss of its benefits and an increase in the costs of delivery. Spectrum is also only one source of additional network capacity, which can also come from technological improvements yielding increased spectrum efficiency, or via the installation of a larger number of cells of various types. The most efficient balance between these sources depends on the nature and volume of the demand to be served and the relative costs of providing capacity via each method. This creates a considerable challenge for Ofcom and other international regulators in balancing the need to take action now to secure the long term opportunity for spectrum to be made available for wireless broadband against the risks associated with allocating either excess or insufficient quantity. This project aims to mitigate these risks via careful analysis of the performance of future wireless technology to meet demand under various conditions relative to the cost of providing it. 1.2 The scope of our study and our approach This study was conducted to support Ofcom s understanding of the techniques available to increase the capacity of wireless broadband networks over the time period 2012 2030. From the outset of this project the key drivers were to improve the understanding of: The extent to which additional spectrum (including the 800 MHz and 2600 MHz frequency bands) will meet future demand over the next 10-15 years.

The role additional spectrum bands might play in meeting this demand, including the release of an additional 500 MHz of spectrum by the public sector, and the ongoing international harmonisation of the 700 MHz band and other higher frequency bands The role of additional sectors and smaller cells The role of more efficient standards such as LTE The potential for offload to Wi-Fi and/or femtocells The role of additional spectrum needed for wireless broadband backhaul capacity During the early stages of the project these drivers were used to identify an overarching question for the project to address, stated as follows: Main study question How much does the addition of 700 MHz and other harmonised spectrum bands affect the scale of the infrastructure and the cost of delivering wireless broadband in the UK using standardized mobile technologies over the period up to 2030 given: Existing mobile spectrum plus 800 MHz and 2600 MHz as a baseline Expected growth in the (spectrum and productive) efficiency of mobile technologies and topologies A range of possible scenarios for the size and nature of UK demand Note that, although our study is focused on the comparative network size and costs of meeting demand according to the available spectrum, this is only part of the value of additional spectrum, which may also: Enable competition Enable innovation Improve user experience by increasing the quality of services which can be economically delivered In order to fully address the main study question, we have developed a methodology to address this question as follows: We created demand growth scenarios for the period 2012-2030 which incorporate the highly non-uniform characteristics of mobile broadband demand by location, device, time of day and user We determined, via an automated optimisation technique, cost-efficient networks to serve the growing demand in a variety of representative areas of the UK, subject to varying assumptions regarding the efficiency of wireless broadband technology and the rate and timing of availability of suitable spectrum. We compared the scale of the infrastructure and the cost of meeting demand over the entire period between scenarios and hence determined the risks and benefits of varying levels of spectrum release, especially regarding both 700 MHz and higher frequency (above 1 GHz) spectrum. This report describes in detail the methodology and assumptions necessary to derive the demand and supply scenarios required to address the key objective of the study. It also presents the outcomes and findings based on a range of scenarios selected to meet Ofcom s requirements. 21

1.3 Sources of capacity Given that our project is concerned with capacity, we have examined the relative merits especially in terms of costs and numbers of sites of creating adequate capacity across a wide range of options. The capacity of any wireless network is a function of three key elements illustrated in Figure 1-1: The spectrum used to deliver the service The technology which delivers bits over the air The topology of the cells which comprise the network TECHNOLOGY SPECTRUM Capacity TOPOLOGY Figure 1-1: Capacity depends on a combination of spectrum, technology and topology of the network In broad terms, the total network capacity can be expressed as the product of the contributions from these three elements: Capacity = Quantity of spectrum x Cell Spectrum Efficiency x Number of cells [bits per second] [hertz] [bits per second per hertz per [no units] cell] Capacity Spectrum Technology Topology So a gain in any these elements produces acts to enhance the gains in the other two. Demand for wireless is rarely uniform across the area to be served, and limits in capacity appear in localised areas. As a result, it is often more relevant to examine the density of capacity in a small area: Capacity density = Quantity of spectrum x Cell Spectrum Efficiency x Cell density [bits per second per km 2 ] [hertz] [bits per second per hertz per cell] [cells per km 2 ] Capacity Spectrum Technology Topology The right balance between capacity-enhancing techniques in these three categories depends on a range of market- and operator-dependent factors, including the relative cost versus benefit of each technique at a given time. The set of specific capacity-enhancing techniques we have considered is illustrated in Figure 1-2. Where feasible, we have considered the performance of these techniques explicity. In some cases, particularly when considering the long-term future, we have made assumptions based on plausible performance growth rates and considered a range of alternative scenarios to determine the sensitivity of our results to these assumptions. 22

Figure 1-2: Capacity-enhancing techniques considered in this study Spectrum Topology Technology Existing mobile spectrum bands (900, 1800, 2100, 2600, 3500 MHz) New mobile spectrum bands (800, 2600 MHz) Potential public sector spectrum Potential 700 MHz band Macrocells Outdoor small cells (microcells/metrocells) Indoor licencedspectrum small cells for offload (femtocells/picocells) Indoor unlicencedspectrum small cells for offload (e.g. Wi-Fi) Advanced modulation and coding techniques, including LTE-Advanced and its evolutions Antenna techniques, including MIMO/space-time coding Interference management techniques, including CoMP approaches Additional sectorisation 1.4 Our approach In order to credibly determine the costs of meeting potential future demand for wireless services, it is necessary to account for a number of non-uniformities in the current and expected future demand. These non-uniformities include: The variation of demand according to time of day and environment. For example, the busiest part of the day is likely to be different for business districts and residential districts. Sufficient capacity has to be available in the right locations to meet each of these traffic peaks individually. The variation of demand amongst individual users: currently a relatively small percentage of mobile users accounts for the majority of demand, so the locations and spread of these users are relevant to both the need to distribute capacity and to the opportunity to offload traffic to other networks cost-effectively. The balance of demand between indoor and outdoor environments: the majority of demand is currently amongst indoor users, which places extra load and range constraints on outdoor cell sites relative to demand generated outdoors. The variation of demand per device: smartphones consume less data than tablet devices, which in turn consume less than mobile broadband modems. These considerations and others led us to creating the sophisticated modelling framework illustrated in Figure 1-3. The framework determines ultimately the comparative costs, on a regional basis, of meeting wireless demand arising from the deployment of varying timing and quantity of suitable spectrum. We examine the whole of the UK market and costs incurred by society as a whole, rather than examining the view of any individual operator. In our project we work on the assumption that the UK wireless market as a whole will ultimately adopt a rational approach to minimising the cost of meeting a given level of demand, given the mix of spectrum, technology and topology options available at the relevant time. 23

Our modelling is driven by a range of numerical scenarios concerning the following: Demand where we concentrate our attention on wireless demand arising from mobile broadband applications. Spectrum where we include a range of possible outcomes for future harmonised, standardised spectrum in the UK based on guidance from Ofcom. Spectral efficiency where we examine the gains in technology performance arising from known techniques as well as scope for further innovation from techniques as yet unknown. Offload where we allow varying proportions of demand to be served via indoor cells (including femtocells and Wi-Fi) in licenced or unlicenced spectrum. In each case we posit low, medium and high scenarios for these inputs and combine them in various ways. A high-level analysis of these scenarios was conducted to compare the overall scope for growth in available capacity in UK wireless networks with the potential demand to determine the extent to which new cell sites might be required. This high-level analysis does not, however, capture the subtleties of the non-uniformity of demand nor of the relative costs of adding capacity via varying routes. To address these limitations we have created a sophisticated modelling tool which implements the following process: Modelling process For each year of the study period: o Assess the unserved demand, net of offload, in the study area Determine the available spectrum efficiency and associated cost for all potential sources of additional capacity in that year, including adding spectrum, upgrading existing sites and adding new sites (macro and small cell) For each potential source of additional capacity, compare the cost per unit of demand which would be served Select the source which gives the greatest benefit relative to the cost Remove the newly served demand from the requirements o Repeat until all demand is served Repeat until the end of the study period (2030) Assess the overall network costs for the whole period The total costs are then computed for the study area and augmented with potential costs of spectrum and offload. Finally the total costs for each of the study areas are computed out to 2040 on a present value basis with a social discount rate. 24

Figure 1-3: Modelling framework The study regions selected for our analysis are illustrated in Figure 1-4. These were chosen to represent urban, suburban and rural environments between which the capacity/cost tradeoffs are significantly different, but which together additionally comprise a significant portion (around 6%) of the overall UK demand. Rural Lincolnshire Study Area Urb Lon Sub Lon Rur Lincs Total UK Area, Population Demand km2 (million) 38 1.7 3% 322 1.3 2% 6,103 0.7 1% 6,462 3.7 6% 242,900 62.3 100% Suburban London Urban London Figure 1-4: Study regions selected for detailed modelling 1.5 Wireless broadband demand in the UK While most commentators agree that wireless broadband demand is set to rise rapidly in the future, their forecasts differ widely even in the short term (i.e. 5 years) and do not capture the granular details of the location and nature of the demand over the period to 2030 which we require for our modelling. We have thus created a bottom-up demand modelling process, illustrated in Figure 1-5, which allows us to examine the underlying 25

500 450 400 350 300 250 200 150 100 50 0 Informa, UK, core Informa, UK, conservative Informa, UK, aggressive A-M UK implied Cisco UK implied PA Low PA Mid PA High 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 sources of demand by user and device and produce demand maps which include details of: Quantity of demand Variation in demand during the day Variation by location and environment (indoors and outdoors) Variation by individual Variation by device type Expectations for minimum data throughput levels We do not set out to accurately forecast demand. Instead we examine a wide range of potential demand scenarios to capture plausible outcomes at a varying level of challenge, which are consistent where appropriate with current and near-term forecasts from other sources. UK geographical data Delivery addresses (home and business) by postcode Postprocessing Statistical distributions by geotype Purpose model Road and Rail vectors Passenger and vehicle numbers by route Processing Aggregated demand forecasts Data Demand (petabytes per month) Calibration vs. other forecasts Geotype Clutter raster data Demand Maps Reporting Device adoption by type Data generated/accepted per device type Location type (e.g. indoor/outdoor, home/office, pedestrian/vehicular) Variation in traffic throughout the day Forecast evolution of demand elements (for period 2012-2030) Distribution of traffic amongst users Figure 1-5: Process for modelling demand scenarios Following this process we have created maps of demand for each of our study regions for each year of the study period, as illustrated in Figure 1-7for our mid demand scenario. Note that these are only aggregate views of the demand used by the model, which also has access to specific locations and the nature of the demand. The demand arising from our model for the whole of the UK is shown in Figure 1-8 for all three scenarios and compared with scenarios prepared for Ofcom in 2009 [ xvi ]. The growth in demand over the study period varies from 23x to 297x.Given this wide range, it is important that flexibility is retained by both Ofcom and by operators in order to ensure that capacity can be efficiently delivered if higher growth scenarios arise, while not limiting the value of other potential usage of that capacity if the demand is nearer the lower end of this range. In any case, the need for significantly more capacity than available today is apparent, and the costs of delivering that capacity must be low enough to maximise the net benefits to society and also to support a case for ongoing investment by the industry. Clearly in practice the actual demand supported will depend on the costs of delivery and the associated pricing, but that interaction is beyond the scope of the present study. 26

Figure 1-6: UK mobile demand growth scenarios, 2012-2030 Low Mid High 23x 80x 297x Demand density in 2013 Demand density in 2030 Figure 1-7: Illustrative peak demand density maps for study regions, mid demand scenario 27

10000 7443 PB/month 1984 1000 575 100 10 25 rw high PA High rw mid PA Mid rw low PA Low 1 2010 2015 2020 2025 2030 Figure 1-8: Total UK personal mobile demand (petabytes per month) arising from our scenarios, compared with scenarios used in previous Ofcom studies Demand, Mbps 10,000,000 1,000,000 100,000 10,000 2010 2015 2020 2025 2030 Urban High Urban All Mid Urban Low Suburban High Suburban All Mid Suburban Low Rural High Rural All Mid Rural Low Figure 1-9: Demand growth across scenarios for urban, suburban and rural study areas 1.6 Data offload scenarios Data offload can be used as a method of transferring the data traffic that would be ordinarily generated on the cellular network, i.e. from devices that are normally connected to the cellular network, to the fixed network via a femtocell or Wi-Fi service for example. We assume that a portion of the demand which takes place within indoor environments can be offloaded by these means and therefore no longer needs to be served by the external network. 28

Figure 1-10 shows the growth in the total proportion of the demand offloaded over time used within the model for the low, mid and high scenarios which grow at the following rates. The low case grows by 4% over the whole timeframe The mid case grows by 8% over the whole timeframe The high case grows by 18% over the whole timeframe The offload in rural clutter types was 10% less than the urban/suburban clutter types. The starting point in 2012 was based on existing data and analyst forecasts for growth. The model determines the minimum number of indoor locations at which offload devices would need to be available to deliver this proportion of overall demand and uses this to determine the required number of offloaded devices and the associated costs. However we do not treat this cost as part of the cost optimisation, since a significant portion of this will be incurred anyway as part of other services which the users access. The extent to which the offloaded is targeted as effectively as we have assumed is an uncertainty, as is the potential that consumers (or operators) would be more likely to deploy devices where service quality from the outdoor network is limited. No explicit spectrum allowance is made for offload. It is assumed that offload devices would either operate in licence-exempt spectrum (as in the case of Wi-Fi) or in licenced spectrum in a way which does not significantly increase the overall spectrum requirement, either by successfully coordinating with macrocells in the same channels or else in dedicated channels either operator-specific or shared across the market with a high level of frequency reuse. Given these open questions, this represents an area where further study should be conducted. Nevertheless, we have accounted for levels of offload which are consistent with current trends and note that even if offload levels were half those which we have assumed, this would be well within the range of the demand scenarios we have examined. 100% % of traffic offloaded at demand locations within study area 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 High Urban/Suburban Mid Urban/Suburban Low Urban/Suburban High Rural Mid Rural Low Rural Cisco VNI 2011 Figure 1-10 Assumed growth in offload of indoor traffic (proportion of total demand) for urban, suburban and rural areas 29

1.7 UK spectrum scenarios In establishing the potential future supply of UK spectrum, we have consulted closely with Ofcom regarding the range of cases of interest. Our main interest lies in the period well beyond the forthcoming award of 800 MHz and 2.6 GHz spectrum so these bands are assumed to be available in all scenarios. Our scenarios vary in two main respects: Spectrum below 1 GHz: we examine three cases: o No new 1 GHz spectrum beyond existing 800 and 900 MHz bands o A 700 MHz spectrum band becoming available in 2020 o A 700 MHz spectrum band becoming available in 2026 Spectrum bands above 1 GHz: A varying rate of growth in spectrum bands between low, medium and high scenarios depending primarily on the rate at which public sector spectrum holdings become available for use in mobile services. We also include a late PS case where the 3.4 GHz and the 2.3 GHz bands are delayed relative to the low case by a further 7 years and where the 2010-2025 MHz band is not available. The proportion of spectrum which comes from public spectrum sources varies amongst these scenarios from 11% ( low PS ) via 22% (medium) to 24% (high). In each case, we have explicitly analysed the available bands which make up the total quantity of spectrum. We have assumed that downlink capacity is likely to be the major constraint on total capacity. We estimated the rate at which bands could become available for broadband wireless applications, given the need for harmonisation and associated standardisation to be viable. We factored in the need to refarm some bands from existing usage. Following these considerations, we arrive at a set of scenarios for the net available downlink spectrum by band. The result is shown for our medium (mid) scenario in Figure 1-11. Available net downlink bandwidth (MHz) 700 600 500 400 300 200 100 0 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 3600 MHz -3800 MHz 3600 MHz -3800 MHz 2600MHz (unpaired) 2300 MHz (2310-2390 MHz) 2100 MHz TDD (2010-2025 MHz) 2100 MHZ TDD (1900-1920 MHz) 1452-1492 MHz 3400 MHz - 3600 MHz 3400 MHz - 3600 MHz 2600 MHz 2100 MHz 1800 MHz 900 MHz 800 MHz 700 MHz in 2026 Figure 1-11: Illustrative spectrum scenario, representing the available harmonised standardised spectrum for downlink traffic over the study period. Mid scenario, with 700 MHz available from 2026 The full set of spectrum scenarios is illustrated in Figure 1-13. It is apparent that the 700 MHz band represents only a relatively small proportion of the overall spectrum supply at the end of the period, varying between 5% (high scenario) and 9% (low scenario) of the total by 2030. However it represents some 38% of the relevant spectrum below 1 GHz, so 30

the extent of difference in the physical properties between spectrum bands is expected to be decisive in the impact of 700 MHz. Figure 1-12: UK mobile spectrum supply growth, 2012-2030 Low Mid High 7x 11x 13x Available net downlink specttrum (MHz) 900 800 700 600 500 400 300 200 100 0 65 13x 11x 7x 764.1 654 424.85 411.5 Total 'More' spectrum Total 'Mid' spectrum Total 'Low' spectrum Total 'late PS' spectrum Availability of 700 MHz in 2020 Availability of 700 MHz in 2026 Figure 1-13: Comparison of spectrum scenarios When analysing the properties of spectrum, we have grouped bands into three categories with broadly similar characteristics: Less than 1 GHz Between 1 GHz and 2.1 GHz 2.1 GHz and above We account explicitly for the costs of adding a band to a site, even within one category. 1.8 Spectrum efficiency Wireless technology is expected to deliver substantial gains in spectral efficiency over the next few years due to the advent of enhancements to 3G technology and developments into LTE and LTE-Advanced technology. We studied these advances in a previous project [ viii ] and have used this as the starting point for our work here. However, that project had a shorter timeline and did not consider the costs associated with each potential technical advancement. We have filled those gaps via the process illustrated in Figure 1-14. We have considered the available spectrum efficiency arising from known 3GPP technology releases and projected trends towards the future. The efficiencies are weighted and combined according to the proportion of spectrum likely to be associated with each technology over time. The efficiency achieved depends also on the capabilities of the mobile devices in the market at a given time, and we have modelled the trends here, especially the opportunity to include more antennas and hence achieve gains from MIMO/space-time processing. 31

A range of cell site configurations are individually modelled, including the extent of sectorisation and MIMO applied. Combining these views provides a scenario for the overall spectral efficiency achievable from a given site type in a given environment over time. The spectral efficiency varies by geotype (urban/suburban/rural) and carrier frequency. Three scenarios are examined: Low (little further growth): Where trends in current day mobile broadband technology are already approaching the limits of what is achievable in terms of site spectral efficiency, although the changing mix of device capabilities provides some gains over time. Mid (steady growth): A steady growth case, representing a steady improvement in site spectral efficiency, as algorithms improve and new techniques are introduced to co-ordinate and reduce the interference which ultimately limits cell throughput. High (innovation dividend): represents a significant leap forward in the spectral efficiency mobile broadband technologies. Although we cannot specify exactly how this will come about, the actual efficiency figures are based on a significant improvement over the steady growth case Scenario ITU UMa, Antennas CS,CB Comp Cell SE, UE ants bps/hz/cell 2 4 8 2 1.09 1.51 1.81 4 1.34 1.87 2.24 8 1.71 2.38 2.85 enb ants Evolving MHz per Generation Evolving antenna Count per Device Evolving Site Spectral Efficiency Site Configuration Site Name Sectors Base Tx Macro 3 2 Macro 3 4 Macro 3 8 Macro 6 2 Outdoor Small cell 1-2 2-4 Environmental Scaling Figure 1-14: Process for determining evolution of spectrum efficiency for UK mobile networks The outcome for one site type (macrocells with three sectors and two antennas per sector) is shown in Figure 1-16, representing a growth of between 3.3 and 10.1 times over the study period. Additional growth is available albeit at a cost and with limitations in the potential to upgrade in some cases from greater numbers of antennas on these sites. Figure 1-15: Site spectral efficiency growth, 2012-2030, for three-sector two-antenna macrocells Low Mid High 3.3x 6.2x 10.1x 32

bps/hz/site 18 16 14 12 10 8 6 4 2 0 2010 2011 2012 1.64 2013 2014 High Mid Low 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 16.7 10.2 5.36 1.9 Site ranges Figure 1-16: Site spectral efficiency for three-sector, 2 antenna macrocell site The spectrum band and site type affects the maximum site range as well as its potential spectral efficiency, limiting the number of users who can be delivered with service from that site. We have computed the maximum potential site ranges for a wide range of variables, factoring in both downlink and uplink assumptions. In practice, a site may not achieve its maximum range if it becomes capacity constrained at a shorter range, in which case we assume that the site serves the closest traffic by preference. Site ranges were computed for all combinations of the parameters shown in Figure 1-17. Note that we assume that the minimum data rate which will be considered acceptable can increase with time, causing a downward pressure on site ranges. This is offset to some extent by the opportunity for devices to support wider maximum spectrum bandwidths. Figure 1-17: Parameters for site range calculations Combinations of site range parameters Clutter type: Rural, Urban, Suburban Demand type: Indoor and Outdoor demand Frequencies: Sub 1GHz, 1-2.1 GHz and >2.1GHz Link direction: Uplink and Downlink Site type: a) Macro cells 3 sectors 2 antennas, b) Macro cells 3 sectors 4 antennas, c) Macro cells 3 sectors 8 antennas, d) Macro cells 6 sectors 2 antennas, e) Small cells 1-2 sectors 2-4 antennas Year: Time evolving ranges depending on minimum acceptable user data rate and device bandwidth in the uplink and downlink over the period 2012-2030 33

1.10 Network costs We consider only network (rather than retail) costs in our work, but include: Annual operating costs associated with cell sites of all types Capital expenditure for new equipment Capital expenditure for replacement investment. Cost trends and equipment replacement cycles are considered over the whole of the study period (2012-2030). To avoid any bias against elements of expenditure towards the end of the study period, we extend the cost model for an additional 10 years, but only measure the on-going costs of the existing network beyond 2030. The capacity-enhancing techniques that we explicitly model comprise a number of macrocell related costs, including upgrades to macrocell technology, the deployment of outdoor small cells and the deployment of additional spectrum bands. These costs, illustrated in Figure 1-18, are used in the technical model to drive cost-efficient decisions on which techniques to use. Indoor small cells are modelled through their impact on demand i.e. demand is off-loaded from the public mobile network to an assumed level appropriate to the scenario in question and a cost is assigned to this. Spectrum costs are considered outside the model, since decisions on the spectrum used are based on a long time-period. Additionally, the cost of spectrum to operators does not represent an overall cost to society. Basis for macrocell densification Higher order MIMO Increased sectorisation New build A -3 sector 2Tx MIMO B -3 sector 4Tx MIMO C -3 sector 8Tx MIMO D -6 sector 2Tx MIMO Explicit technology upgrade From A to B Antennas, cabling, civil works From B to C Antennas, cabling, civil works From A to D Antennas, cabling, civil works Implicit technology upgrades 3G to LTE we assume multi-standard base stations deployed so costs is already accounted for Future 3GPP Releases, Carrier aggregation etc. we assume spread into network by natural replacement cycle, hence cost is implicit Adding spectrum bands Explicit costs incurred base station equipment, antennas, civil works etc. when a new band or bands cannot be accommodated by existing configuration an upgrade will be required for all sites where extra capacity is needed Figure 1-18: Overview of cost modelling process 34

Figure 1-19 summarises the main cost estimates for macrocell densification, higher order MIMO, increased sectorisation, outdoor small cells and adding spectrum bands to existing cells. Thousands 0 50 100 150 Residential femtocell Outdoor small cell 0.1 0 13 New build Upgrade (from 3 sector 2Tx site) Adding a new band to existing site 13 Macrocell densification - standard 0 80 Increased sectorisation: 6 sector site 10 92 Higher order MIMO: 4 Tx site 9 92 Higher order MIMO: 8 Tx site 22 107 Figure 1-19: Costs (present value at 2012) for new sites and site upgrades 1.11 High level comparison of demand and supply Given the demand scenarios and the options for increasing capacity described above, we can compare the anticipated growth in demand against the total potential supply. We do this for each of our study regions individually, given the very different characteristics of these regions. We assume in broad terms that UK mobile networks will become capacity constrained at the end of 2012, given the available technology and number of sites. We use this point in time as a baseline for comparison of growth. For the urban study environment, a set of comparisons is shown in Figure 1-20. In the case of the mid demand scenario, and assuming that capacity (i.e. spectrum absent 700 MHz multiplied by spectrum efficiency) follows the mid scenario, capacity growth exceeds the growth of demand by a comfortable level until around 2024. The advent of the 800 MHz and 2.6 GHz spectrum is a significant element in this capacity (around a factor of 3 in spectrum capacity) in the early years. In the middle period, the additional public sector spectrum is significant in avoiding a capacity scarcity. In the low demand scenario, but with high capacity, capacity outstrips demand by a substantial margin over the whole period, suggesting that some of the technology upgrades envisaged in that scenario may be unnecessary, so the associated costs could be avoided and indeed some of the additional spectrum released may not be essential. By contrast, in the high demand low capacity situation, the available capacity is exhausted by 2017 and beyond that point there would be a significant need to seek other sources of capacity. 35

High demand Mid demand Low demand Low spectrum Mid spectrum High spectrum Low Spectrum efficiency Mid spectrum efficiency High spectrum efficiency Figure 1-20: High-level comparison of demand growth with potential capacity growth 2012-30, assuming no growth in sites In the mid demand, mid capacity case, we next examine what would be required to address the lack of capacity towards the end of the study period. We examine the possibility that the availability of 700 MHz could play a role in this. In Figure 1-21 we divide the available capacity by the demand and multiply by the number of existing macrocell sites in the region. Provided this is less than the 2012 starting point, there is an excess of available capacity (it would not be possible to decommission sites in this period since their contribution to coverage will also be important). As seen previously, in the absence of 700 MHz this is the case until 2024, beyond which additional sites become necessary, or at least a more rapid increase in spectral efficiency, both of which will come at a cost. If 700 MHz were available in 2020, this capacity constraint could be avoided until 2027, but this finding would be sensitive to forecast accuracy. If 700 MHz were not available until 2026, the start time of capacity constraints would be unaffected, although the extent of the constraint is reduced, potentially reducing costs. 350 300 Sites Needed 250 200 150 100 50-2010 2015 2020 2025 2030 4 Urban All Mid Never 3 Urban All Mid 2026 7 Urban All Mid 2020 Figure 1-21: Sites needed to provide capacity for urban study area: mid demand, mid spectrum and mid spectrum efficiency, showing the relative impact of the availability and timing of 700 MHz 36

A similar view emerges when considering the rural and suburban environments in Figure 1-22 and Figure 1-23 respectively: there is a sufficiency of capacity in the low demand/high capacity case for the whole period. In the mid demand, mid capacity case there is sufficient capacity until 2024. In this case 700 MHz has the potential to delay and reduce the cost of additional sites, but the extent of the impact is small and dependent on the precise growth rates. In the high demand, low capacity case, capacity would become heavily constrained after around 3 years, beyond which additional investment in capacity would be needed. Sites Needed 1,000 100 13 Rural High demand low cap Never 12 Rural High demand low cap 2026 2 Rural All Mid Never 8 Rural All Mid 2020 1 Rural All Mid 2026 19 Rural Low demand high cap Never 10 2010 2015 2020 2025 2030 Figure 1-22: Sites needed to provide capacity for rural study area 1,000 Sites Needed 100 15 Suburban High demand low cap Never 14 Suburban High demand low cap 2026 6 Suburban All Mid Never 9 Suburban All Mid 2020 5 Suburban All Mid 2026 10 2010 2015 2020 2025 2030 Figure 1-23: Sites needed to provide capacity for suburban study area 37

Although this indicative, high-level analysis provides a view of the relative growth of demand and supply, it is oversimplistic in several ways: It takes no account of the relative costs of adding capacity via technology, spectrum or topology options. Even in cases where there is a sufficiency of capacity, the presence or absence of given spectrum bands could significantly affect the expenditure required to upgrade the capacity of existing sites at the required rate. It account for capacity in only an aggregate form over the study areas, and does not reflect the potential for very local hotspots of traffic to overload or degrade the quality of the network. It does not reflect the likelihood that future services will require increasing typical data rates as well as quantities, which could require network expansion at a rate which would be strongly influenced by the available spectrum. Particularly in the context of 700 MHz, it treats all spectrum as equal in its impact, and does not reflect the varying coverage properties amongst bands. Our full modelling process addresses all of these points. First we examine the potential special properties of low frequency spectrum. 1.12 The utility of low frequency spectrum The high-level analysis presented above treated all spectrum bands as equivalent, so only the relative quantities of each band play a role in determining capacity. However the physical properties of differing spectrum bands can affect the capacity and associated costs in two ways: First, lower frequency spectrum can permit greater range and better indoor penetration. Although this is a coverage advantage rather than a capacity one, it is very relevant to the cost of providing capacity. It also means that a high capacity site with such spectrum can deliver its capacity to users over a wide area, while a site with the same capacity and only limited range may actually have spare capacity. The relative ranges of macrocells are compared in Figure 1-24.The range advantage of lower frequency spectrum is particularly pronounced for indoor users and for rural environments. 38

25 21.5 20 Maximum site range (km) 15 10 5 12.0 8.4 5.6 3.6 3.4 2.9 2.3 1.7 2.0 0.9 1.2 0.7 12.7 6.4 5.3 3.8 2.7 Outdoor Sub 1 GHz Indoor Sub 1 GHz Outdoor 1-2.1 GHz Indoor 1-2.1 GHz Outdoor >2.1 GHz Indoor >2.1 GHz 0 Sub Lon Urb Lon Rur Lincs Figure 1-24: Maximum site ranges for macrocells by spectrum range and geotype for three sector, 2- antenna macrocells for both indoor and outdoor usage Second, the reduced propagation loss for lower frequency spectrum can have a more direct impact on capacity. A user subject to large losses will consume a larger proportion of system resources in power and spectrum terms, which will limit the remaining capacity for other users. Thus, provided interference between sites is carefully managed, lower frequency spectrum can actually deliver a higher spectral efficiency than higher frequency spectrum. This may seem counterintuitive given that it is typical to consider higher frequency spectrum as more appropriate for high capacity requirements, but in fact this arises simply from the larger quantity of spectrum typically available in the higher bands rather than its intrinsic physical properties. We have conducted investigations on this point using a simulator developed by Ofcom. The gains of spectral efficiency for < 1 GHz spectrum relative to other bands for our urban and rural geotypes are shown in Figure 1-25. For the rural environment the lower frequency spectrum is 47% more efficient than the highest bands for indoor traffic and 18% more efficient for outdoor traffic. The relative gains are lower for outdoor traffic or for urban environments, but can still be substantial. 39

Spectral efficiency advatnage of < 1 GHz spectrum 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 47% 22% 20% 18% 7% 8% 1% 2% Indoor Outdoor Indoor Outdoor Indoor Outdoor Indoor Outdoor 1-2.1 GHz > 2.1 GHz 1-2.1 GHz > 2.1 GHz Rural Urban Figure 1-25: Relative spectral efficiency of < 1 GHz by environment and geotype Taking these two effects together indicates that we should expect 700 MHz to have a proportionately greater impact than would be suggested by its quantity alone. We have incorporated both of these effects within the detailed results which follow. 1.13 Cost-efficient capacity expansion detailed results We now combine together all of the elements previously described to determine the cost efficient delivery of capacity via our modelling process, subject to varying input scenarios. Figure 1-26 provides example results from the model for our rural study region in two scenarios for rural Lincolnshire. Both relate to the mid demand, mid capacity case. In the first column no 700 MHz is available. In the second column, 700 MHz becomes available in 2026. (a) and (b) show how the sites and associated technology evolves. Generally, the period between 2012 and 2017 is characterised by little requirement for additional sites, but an increasing upgrade of existing macro sites from 3 sectors to 6 sectors. This shows generally reasonable agreement with the high-level analysis provided earlier. In this period, existing sites are progressively upgraded to have additional sectors or more antennas to increase their capacity. At the same time the available spectrum bands are used progressively as shown in (c) and (d) and are significant in forestalling the need for earlier build of new sites. However, by 2017 most of the sites which it is worthwhile to upgrade have already been upgraded and little new spectrum is available, so it becomes important to add more capacity via new sites. Some new macrocell sites are added, but the main site additions are small cells, which although providing lower range and lower maximum capacity are nevertheless significantly cheaper and have sufficient coverage to serve localised pockets of excess demand. (e) and (f) show how the varying upgrades are reflected in network costs with a reduction in the required expenditure in (f) compared with (e) as a result of 700 MHz availability. 40

Figure 1-26 represents results from just two runs of our model: overall we included in this report results based on 39 runs of our model, representing combinations of inputs and study regions of relevance to Ofcom s requirements, the main outcomes of which are shown in Table 1-1. As a central case, we examine situations (scenarios 1-6) where the demand, offload, spectrum and spectrum efficiency take their mid values and investigate the impact of availability of 700 MHz in 2026. In scenarios 7-9, also for the mid values for demand and capacity, we determined the impact of 700 MHz becoming available earlier, in 2020. In scenarios 10-15 we determine the impact of 700 MHz availability in cases where the demand is high but the capacity (offload, spectral efficiency and spectrum) is low. In scenarios 16 21 we examine the reverse situation, where the demand is low and the capacity is high. In the remaining 18 scenarios (22-39) we investigate the sensitivities of offload and spectrum by modelling the high and low cases in each. In scenarios 22 27 we model the mid demand with low offload for the 700 MHz in 2020 and never cases and in scenarios 28-33 we model the mid demand with high offload for the 700 MHz in 2020 and never cases. Scenarios 34-39 determine the impact from mid demand with low public sector and high spectrum inputs in the 2020 case across each study area. 41

Table 1-1: Detailed results by scenario Scenario Study region Inputs 700MHz available from Macro sites Cumulative Small cell sites network cost, M Offload Cost, M Spectral Demand Offload efficiency Spectrum in 2012 in 2030 in 2012 in 2030 to 2030 to 2040 to 2030 to 2040 Mid demand and capacity, with and without 700 MHz in 2026 1 Rural M M M M 2026 157 192 7 27 8.2 11.0 25.3 33.4 2 Rural M M M M Never 157 202 7 29 8.9 12.3 25.3 33.4 3 Urban M M M M 2026 95 108 360 426 4.7 6.8 24.4 32.2 4 Urban M M M M Never 95 111 360 481 5.4 8.6 24.4 32.2 5 Suburban M M M M 2026 227 240 10 80 8.6 11.1 41.1 54.2 6 Suburban M M M M Never 227 247 10 162 10.0 14.2 41.1 54.2 Impact of earlier 700MHz availability in 2020 (mid demand and capacity) 7 Urban M M M M 2020 95 106 360 447 3.9 6.2 24.4 32.2 8 Rural M M M M 2020 157 192 7 25 7.8 10.5 25.3 33.4 9 Suburban M M M M 2020 227 236 10 75 6.3 8.4 41.1 54.2 High demand, low capacity cases 10* Urban H L L L 2026 95 179 360 5126 168.0 249.7 22.8 29.4 11* Urban H L L L Never 95 178 360 5425 172.1 258.7 22.8 29.4 12 Rural H L L L 2026 157 931 7 339 82.0 135.7 23.5 30.5 13 Rural H L L L Never 157 1068 7 462 91.8 155.5 23.5 30.5 14 Suburban H L L L 2026 227 1381 10 3934 253.5 409.7 38.1 49.4 15 Suburban H L L L Never 227 1400 10 4616 263.0 430.8 38.1 49.4 Low demand, high capacity cases 16 Urban L H H H 2026 95 95 360 361 0.3 0.3 28.7 38.8 17 Urban L H H H Never 95 95 360 361 0.3 0.3 28.7 38.8 18 Rural L H H H 2026 157 168 7 15 2.4 3.3 30.3 41.1 19 Rural L H H H Never 157 168 7 15 2.4 3.3 30.3 41.1 20 Suburban L H H H 2026 227 227 10 10 0.8 0.8 49.5 67.0 21 Suburban L H H H Never 227 227 10 10 0.8 0.8 49.5 67.0 Mid demand, high/low offload cases 22 Rural M L M M 2020 157 189 7 48 8.0 10.9 23.0 29.9 23 Rural M L M M Never 157 199 7 40 8.9 12.4 23.0 29.9 24 Urban M L M M 2020 95 108 360 453 4.5 7.0 22.5 29.3 25 Urban M L M M Never 95 114 360 485 5.9 9.4 22.5 29.3 26 Suburban M L M M 2020 227 237 10 118 7.5 10.3 37.3 48.5 27 Suburban M L M M Never 227 252 10 179 10.8 15.6 37.3 48.5 28 Rural M H M M 2020 157 187 7 25 7.2 9.7 30.3 41.1 29 Rural M H M M Never 157 199 7 24 8.2 11.4 30.3 41.1 30 Urban M H M M 2020 95 100 360 423 3.3 4.7 28.7 38.8 31 Urban M H M M Never 95 103 360 485 4.7 7.3 28.7 38.8 32 Suburban M H M M 2020 227 230 10 45 5.1 6.3 49.5 67.0 33 Suburban M H M M Never 227 236 10 132 7.8 10.8 49.5 67.0 Mid demand, high/low spectrum cases 34 Rural M M M H 2020 157 188 7 25 7.2 9.7 25.3 33.4 35 Rural M M M L 2020 157 192 7 37 7.9 10.8 25.3 33.4 36 Urban M M M H 2020 95 98 360 400 2.2 3.2 24.4 32.2 37 Urban M M M L 2020 95 132 360 611 14.5 21.7 24.4 32.2 38 Suburban M M M H 2020 227 231 10 59 5.3 6.8 41.1 54.2 39 Suburban M M M L 2020 227 292 10 158 15.0 22.5 41.1 54.2 Note *: Scenarios 10 and 11 were unable to meet demand in last years of the study period as limits of site spacing reached. Results presented are based on the outcomes at 2027. 42

250 Outdoor small cell, 1-2 sectors, 2-4 antennas 250 Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas Macro, 6 sectors, 2 antennas 200 Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas 200 Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas Number of sites 150 100 Number of sites 150 100 50 50 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 a) Sites & Upgrades Rural Lincs no 700MHz 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 b) Sites & Upgrades Rural Lincs 700MHz in 2026 300 300 3600 MHz -3800 MHz 3600 MHz -3800 MHz Average bandwidth used per macro site (MHz) 250 200 150 100 50 3600 MHz -3800 MHz (UKB) 2700-3100 MHz 2600MHz 2300 MHz (2310-2390 MHz) 2100 MHz TDD (2010-2025 MHz) 2100 MHZ TDD (1900-1920 MHz) 1452-1492 MHz 3400 MHz - 3600 MHz 3400 MHz - 3600 MHz (UKB) 2600 MHz 2100 MHz 1900 MHz (1980-2010 MHz) 1800 MHz Average bandwidth used per macro site (MHz) 250 200 150 100 50 3600 MHz -3800 MHz (UKB) 2700-3100 MHz 2600MHz 2300 MHz (2310-2390 MHz) 2100 MHz TDD (2010-2025 MHz) 2100 MHZ TDD (1900-1920 MHz) 1452-1492 MHz 3400 MHz - 3600 MHz 3400 MHz - 3600 MHz (UKB) 2600 MHz 2100 MHz 1900 MHz (1980-2010 MHz) 1800 MHz 900 MHz 900 MHz 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 800 MHz 700 MHz 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 800 MHz 700 MHz c) Band Utilisation d) Band Utilisation Rural Lincs, no 700MHz Rural Lincs, 700MHz in 2026 e) Total Cost of Ownership Rural Lincs, no 700MHz f) Total Cost of Ownership Rural Lincs, 700MHz in 2026 Figure 1-26: Comparing the evolution of sites, spectrum utilisation and costs for rural study area (mid demand and capacity) 1.13.1 Mid Demand, Mid Capacity Scenarios For the mid-demand, mid capacity cases, Figure 1-27 shows how the required number of macrocell and small cell sites varies over the study period and the associated influence of 700 MHz. Figure 1-28 shows the associated variation in network costs. Rather different behaviour is encountered in each of the study areas, which are discussed individually below. 43

Number of macro sites, relative to 2012 x1.35 x1.30 x1.25 x1.20 x1.15 x1.10 x1.05 Rur Lincs, Never Rur Lincs, 2026 Rur Lincs, 2020 Sub Lon, Never Sub Lon, 2026 Sub Lon, 2020 Urb Lon, Never Urb Lon, 2026 Urb Lon, 2020 x1.00 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 Number of small cells 2029 2030 600 500 400 300 200 Rur Lincs, Never Rur Lincs, 2026 Rur Lincs, 2020 Sub Lon, Never Sub Lon, 2026 Sub Lon, 2020 Urb Lon, Never Urb Lon, 2026 Urb Lon, 2020 Macrocells 100 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Small Cells Figure 1-27: Influence of 700 MHz availability on growth in cell sites for mid demand, mid capacity scenarios 44

Millions 10 9 8 7 6 5 4 3 2 1 0 High demand Mid demand Low demand Rur Lincs, 2026 Rur Lincs, Never Rur Lincs, 2020 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 (a) Rural Millions 10 9 8 7 6 5 4 3 2 1 0 High demand Sub Lon, 2026 Sub Lon, Never Sub Lon, 2020 Mid demand Low demand 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 (b) Suburban 6.0 5.0 4.0 3.0 2.0 High demand Urb Lon, 2026 Urb Lon, Never Urb Lon, 2020 Mid demand 1.0 Low demand 0.0 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Millions 2023 2024 2025 2026 2027 2028 2029 2030 (c) Urban Figure 1-28: Influence of 700 MHz availability on cumulative network costs (present value at 2012) for scenarios 1 to 21. High demand case is with low capacity, low demand is with high capacity 45

Rural Area, Mid Demand and Capacity In the rural area, Figure 1-27 shows that the number of macrocells grows fairly steadily over the period from 2017, as coverage requirements increase beyond that which can be delivered using existing sites. The rate of increase of these sites is reduced by the availability of 700 MHz, since it increases the capacity available to handle traffic on bands providing wide area coverage, notably those below 1 GHz. The number of small cells also grows over the period, absorbing local hot spots of capacity which would otherwise require relatively more costly macrocells. The timing of 700 MHz plays a significant role, with 2020 availability extending the period over which the number of sites is reduced. As a result 700 MHz reduces the number of new macrocell sites required over the study period by 22% whether available in 2026 or in 2020. It is notable however that towards the end of the period the difference in total sites is reduced as the need for capacity becomes a more dominant driver than that for overall coverage, and the rate of small cell growth increases. Figure 1-28 shows the rate of increase in costs reduces from the advent of 700 MHz and the reduced rate endures over the whole period, resulting in a network cost saving of 11% (2026) and 15% (2020). So in the rural area, 700 MHz brings a cost saving of 11%, considerably larger than the 6% which would be expected based on the quantity of spectrum alone, especially given the limited period over which it can take effect. The benefit in cost terms is increased to 15% if it can be made available earlier, forestalling the need to build extra macrocells and extra small cells. It is notable however that a growth of the number of cells is required even with 700 MHz, notably in the case of small cells which increase by around 4.5x over the study period. Urban Area, Mid Demand and Capacity In the urban study area, Figure 1-27 shows significant increases in the required number of macrocells in the period after 2022. This arises from capacity constraints, where the existing macrocells are unable to deliver sufficient capacity and have already been upgraded to achieve the highest possible level of spectrum efficiency. The excess demand is distributed over a relatively wide area, so although small cells serve a significant and growing quantity of demand[ 1 ] it is still cost effective to deploy additional macrocells. The availability of 700 MHz in 2020 delays the capacity crunch by several years and reduces the number of sites needed beyond that by 28%. Figure 1-28 (c) shows that the availability of 700 MHz brings substantial network cost savings of around 21% in the case of 2026 availability. It happens that in this scenario 2026 availability is well-timed to forestall a capacity crunch which would otherwise occur in this year. The result is that early (2020) availability has a somewhat less pronounced effect than in the rural case but is still notable at around 28%. Suburban Area, Mid Demand and Capacity Figure 1-27 shows that the suburban area follows a somewhat similar pattern to the urban case, with a capacity crunch occurring from around 2023. However, in this case, although this leads to some more macrocell build, in this case the majority of additional capacity comes from new small cells, which occurs because the demand is more spatially variable, making small cells the most cost-effective means of providing additional capacity. Use of 700 MHz from 2026 avoids the need for many of these small cells, 1 Around 20% of the demand is served by outdoor small cells over most of the study period. 46

reducing the number of additional cells in total by 52%. Nevertheless, the number of small cells is still substantial growing by around 8 times in the 2026 case. Interestingly, if 700 MHz is available in 2020, this actually makes it more cost effective to build more small cells than the 2026 case, and the combination of 700 MHz (for wide area capacity) and small cells (for localised hotspots) almost entirely avoids the need to build additional macrocells. In cost terms, Figure 1-28 (b) shows the availability of 700 MHz in 2026 reduces network costs by some 21%, increasing to 41% if available from 2020. 47

Relative site and cost saving from the availability of 700 MHz The results of our mid-demand, mid-capacity scenarios are summarised in terms of the relative site and network cost savings arising from 700 MHz availability in Figure 1-29 below. Saving (relative to no 700 MHz) 60% 50% 40% 30% 20% 10% 21% 19% 42% 31% 28% 28% 21% 35% 52% 41% 55% 57% Network Cost saving (to 2040) New site saving (macro) New site saving (total) 22% 22% 21% 18% 15% 11% 0% 2026 2020 2026 2020 2026 2020 Urban Suburban Rural Figure 1-29: Relative savings in network costs (to 2040) and new cell sites (by 2030) arising from the availability of 700 MHz in 2020 or 2026 (mid demand and mid capacity scenarios) 1.13.2 The action of 700 MHz in delaying a capacity crunch To provide additional insight into the role which 700 MHz plays in contributing to capacity, Figure 1-30 shows the band utilisation across the low (<1 GHz), medium (1-2.1 GHz) and high (>2.1 GHz) frequency groups for the 700 MHz timing sensitivity with medium demand and capacity. The band utilisation indicates the proportion of the demand served by the network which flows over each of the groups of bands relative to the total capacity they could be capable of given the number of sites and spectrum efficiency at the time. When the utilisation is very high, the cell size shrinks rapidly, leading to a requirement to build more cell sites and a form of spectrum saturation. In the suburban and rural areas the low frequency spectrum tends to rise in utilisation most rapidly amongst the groups of bands, while in the urban area all bands becomes rapidly utilised to meet the growing demand density. In all cases, however, it is the low frequency bands which reach saturation first in the absence of 700 MHz. The presence of 700 MHz produces a sudden reduction in utilisation, forestalling the spectrum crunch and avoiding the need to build as many new sites. The band quickly becomes utilised to take advantage of its properties, but it has the effect of substantially delaying the advent of the spectrum crunch and reducing the subsequent rate of new site builds. However in the suburban and urban cases, the spectrum has already become saturated by 2026 so the advent of 700 MHz at that point has relatively less impact than making it available in 2020 when there is still scope to avoid saturation. 48

Utilisation of high/med/low bands 100% 90% 80% 70% 60% 50% 40% 30% 20% Spectrum crunch Rapid cell build activity 700 MHz available 700 MHz available Low f 2020 Med f 2020 High f 2020 Low f 2026 Med f 2026 High f 2026 Low f Never Med f Never High f Never 10% 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 (a) Rural Utilisation of high/med/low bands 100% 90% 80% 70% 60% 50% 40% Spectrum crunch Rapid cell building activity 700 MHz available 700 MHz available Low f 2020 Med f 2020 High f 2020 Low f 2026 Med f 2026 High f 2026 Low f Never Med f Never High f Never 30% 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 (b) Suburban 49

Utilisation of high/med/low bands 100% 90% 80% 70% 60% 50% 40% Spectrum crunch Rapid cell building activity 700 MHz available 700 MHz available Low f 2020 Med f 2020 High f 2020 Low f 2026 Med f 2026 High f 2026 Low f Never Med f Never High f Never 30% 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 (c) Urban Figure 1-30 Utilisation of low medium and high frequency bands, with varying 700 MHz timing, medium demand and capacity 50

1.13.3 High Demand, Low Capacity Scenarios Number of macro sites 1400 1200 1000 800 600 400 200 Rur Lincs, Never Rur Lincs, 2026 Sub Lon, Never Sub Lon, 2026 Urb Lon, Never Urb Lon, 2026 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Number of small cells 6000 5000 4000 3000 2000 1000 Macrocells Rur Lincs, Never Rur Lincs, 2026 Sub Lon, Never Sub Lon, 2026 Urb Lon, Never Urb Lon, 2026 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Small Cells Figure 1-31: Influence of 700 MHz availability on growth in cell sites for high demand, low capacity scenarios Figure 1-31 includes results for the high demand, low capacity scenarios, where demand grows at the highest rate considered while spectrum, spectrum efficiency, offload and spectrum are all in their lowest scenarios. In all three study areas, this results in a dramatic shortfall of capacity based on existing sites and a large-scale site build programme ensues to meet the shortfall. The large site build programme indicated is likely to be unrealistic. The resulting costs, as illustrated in, Figure 1-28 are also very large and likely to be unaffordable to consumers. Our detailed analysis includes consideration of this affordability point. In this situation the advent of 700 MHz in 2026 does yield a cost and site saving as indicated in Figure 1-28. In the rural area, where coverage is a significant driver, the cost savings are high compared with the quantity of spectrum at 700 MHz. In the urban and rural areas, where capacity limitations are dominant, the cost savings of 5% and 3% respectively are more consistent with the quantity of spectrum. 51

1.13.4 Low Demand, High Capacity Scenarios In the case where demand grows at the lowest rate considered and all capacity elements (spectrum, offload and spectrum efficiency) grow at their highest rates, Figure 1-28 indicates that the opportunity for cost saving is low. While some additional sites are needed in the rural area to enhance coverage, no new sites (macro or small) are needed in the urban and suburban environments and site technology upgrades are sufficient to meet the capacity requirements. Additional spectrum is not required, and no savings occur as a result of the availability of 700 MHz. 1.13.5 Offload sensitivity analysis We assume that offload in suburban and urban areas is currently around 40% of total traffic and will grow over the study period to 50% in our mid scenario (and a somewhat lower level in rural areas). Such an apparently modest growth in the fraction offloaded actually represents a very substantial growth in the volume of traffic, given the underlying total demand growth. It could be, therefore, that in practice the volume of offload is limited, or that practical factors such as backhaul capability and the need to target devices for the most needy locations limit the level of offload relative to our assumptions. Figure 1-32 shows how the number of cell sites which need to be built is influenced by the amount of indoor traffic offloaded, and the consequent network costs (which do not include the cost of the necessary offload devices) are shown in Figure 1-33 The fraction of traffic offloaded is reduced to 45 % by 2030 in our low scenario, and 60 % in our high scenario. 52

250 230 Number of macro sites 210 190 170 150 130 110 Rur Lincs, HighOff,2020 Rur Lincs, LowOff,2020 Rur Lincs, MidOff,2020 Sub Lon, HighOff,2020 Sub Lon, LowOff,2020 Sub Lon, MidOff,2020 Urb Lon, HighOff,2020 Urb Lon, LowOff,2020 Urb Lon, MidOff,2020 90 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Macrocells 2022 2023 2024 2025 2026 2027 2028 2029 2030 455 405 Number of macro sites 355 305 255 205 155 105 55 Rur Lincs, HighOff,2020 Rur Lincs, LowOff,2020 Rur Lincs, MidOff,2020 Sub Lon, HighOff,2020 Sub Lon, LowOff,2020 Sub Lon, MidOff,2020 Urb Lon, HighOff,2020 Urb Lon, LowOff,2020 Urb Lon, MidOff,2020 5 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Small Cells Figure 1-32: Influence of varying offload on growth in cell sites for mid demand, and mid capacity (spectrum, spectrum efficiency) with 700 MHz in 2020 2022 2023 2024 2025 2026 2027 2028 2029 2030 53

Millions 8 Rur Lincs, 2020,HighOff 7 Rur Lincs, 2020,MidOff 6 Rur Lincs, 2020,LowOff 5 4 3 2 1 0 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 (a) Rural Millions 10 9 8 7 6 5 4 3 2 1 0 2013 2014 2015 2016 Sub Lon, 2020,HighOff Sub Lon, 2020,MidOff Sub Lon, 2020,LowOff 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Millions 8 7 6 5 4 3 2 1 0 2013 2014 2015 (b) Suburban Urb Lon, 2020,HighOff Urb Lon, 2020,MidOff Urb Lon, 2020,LowOff 2016 2017 2018 2019 2020 2021 2022 (c) Urban 2023 2024 2025 Figure 1-33: Influence of varying offload on growth in costs for mid demand, and mid capacity (spectrum, spectrum efficiency) with 700 MHz in 2020 2026 2027 2028 2029 2030 54

Figure 1-34 shows that varying the potential level of offload (to 45 % by 2030 in our low scenario, and 60 % in our high scenario) varies the network costs, with a higher cost to meet the same demand to compensate for lower offload. Figure 1-35 shows that lower offload also increases the number of cell sites needed. In all of our study environments, however, the network costs with the lowest level of offload in the presence of 700 MHz (in 2020) are still lower than those incurred with the highest level of offload in the absence of 700 MHz. Thus the presence of 700 MHz can reduce the necessary level of offload (and further reduce the associated costs of establishing and running the offload devices, which are not included in this comparison) or indeed can make a given level of offload more effective overall. Network costs to 2040 ( m) 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0-7.0 6.2 Lo Med 4.7 Hi 9.4 8.6 7.3 Lo Med Hi 10.3 Lo 8.4 Med 6.3 Hi 15.6 14.2 Lo Med 12.4 12.3 10.8 10.9 11.4 10.5 9.7 Hi Lo Med Hi Lo Med 2020 Never 2020 Never 2020 Never Urban Urban Suburban Suburban Rural Rural Hi Figure 1-34: Impact of varying offload assumptions on network costs (to 2040), with and without availability of 700 MHz in 2020 (mid demand and mid capacity scenarios). Costs should be treated as illustrative and relative rather than absolute. 55

700 No. of cell sites 600 500 400 300 200 100 0 453447 423 485481485 118 75 45 179 162132 108106100114111103 Lo Med Hi Lo Med Hi 48 25 25 40 29 24 237236230 252247 236 189192187 199202199 Lo Med small cells in '30 macros in '30 Hi Lo Med Hi Lo Med Hi Lo Med Hi 2020 Never 2020 Never 2020 Never Urban Urban Suburban Suburban Rural Rural Figure 1-35: Impact of varying offload assumptions on cell sites (in 2030), with and without availability of 700 MHz in 2020 (mid demand and mid capacity scenarios) 1.13.6 Spectrum sensitivity analysis A substantial portion of the spectrum growth represented in our mid-case spectrum scenario is from public sector spectrum holdings, representing some 22% of the total relevant spectrum by 2030. Here we investigate how changing that assumption affects the supply of capacity. In our high spectrum scenario we show the impact on the network costs of that spectrum becoming available more rapidly, reaching 24% of relevant spectrum or at a slower rate ( late pub. sect ), where it represents only 11% of spectrum in 2030. In all cases, 700 MHz is assumed to be available from 2020. Rural Area, Mid Demand/Capacity and Low/High spectrum Figure 1-36 shows how the number of sites varies over the study period in response to changes in the quantity of spectrum available, with other parameters at their mid-scenario values. In the rural area the quantity of spectrum does not play a strong role in the required number of sites, either for macrocells or small cells. This arises because the prime driver for the number of cell sites in this area is the required coverage, while the additional spectrum comes mainly from public sector sources above 1 GHz which do not contribute to improved coverage. The associated network costs shown in Figure 1-37(a) also show relatively little variation with the quantity of spectrum, although there is some saving by the end of the period in the high case. The changing ordering of the scenarios results from minor variations in the decisions made in the optimisation process and further indicates the lack of sensivity. 56

Urban Area, Mid Demand and Low/high spectrum In the urban area, Figure 1-36 indicates that the quantity of spectrum available plays a strong role in determining the number of both macrocells and small cells deployed. A spectrum crunch starts to occur around 2018 with the low spectrum scenario and the number of macrocells starts to increase rapidly. There is a steady increase from 2019 to 2023 in the number of new macrocells required in the low spectrum scenario as demand is served, and an additional capacity crunch appears between 2023 and 2024 when an increase in macrocells is required. The effects can also be seen in the small cells which show the capacity crunch starting in 2023 continuing to the end of the period resulting in a 70% increase in the number of required new small cells. The impact the low spectrum scenario has on cost in Figure 1-37 is striking compared to the mid and high cases. The requirement for both additional macrocells and small cells as well as other sites upgrades means a steep increase in network costs between 2019 and 2025 to relieve the capacity crunch. This is consistent with the requirement for the widespread use of techniques to deliver a high demand density in the urban area. Suburban Area, Mid Demand and Low/high spectrum The suburban area exhibits similar overall behaviour to the urban area as regards both costs and sites, with the occurrence of a pronounced capacity crunch. However, Figure 1-36 shows that the advent of the capacity crunch occurs later compared to the urban area. In the case of additional macrocells, new sites are required around 2024 compared to 2019 in the urban area. This means spectrum, and particularly sub 1 GHz spectrum is able to delay the capacity crunch due to both the wide area coverage and available bandwidth. The pattern can also be seen in the number of small cells. In 2024 the number of additional small cells starts to increase and by 2030 there is almost a 4-fold increase in small cells. The small cells serve localised pockets of especially high demand density, relieving the macrocells to serve the residual demand which is then more uniform over a wider area. The cost implications, as seen in Figure 1-37(b), compare with the urban case in that the low spectrum scenario costs increase rapidly over a 3 to 4 year period to satisfy the capacity crunch and rate of increase reduced slightly for the remaining 4 to 5 years as the public sector spectrum that does become available very quickly gets used up and sites continue to be built. 57

Number of macro sites 340 290 240 190 Rur Lincs High spectrum 2020 Rur Lincs less PS spectrum 2020 Rur Lincs mid spectrum 2020 Sub Lon high spectrum 2020 Sub Lon mid spectrum 2020 Sub Lon less PS spectrum 2020 Urb Lon high spectrum 2020 Urb Lon mid spectrum 2020 Urb Lon less PS spectrum 2020 140 90 Number of macro sites 705 605 505 405 305 205 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Macrocells Rur Lincs high spectrum 2020 Rur Lincs mid spectrum 2020 Rur Lincs less PS spectrum 2020 Sub Lon high spectrum 2020 Sub Lon mid spectrum 2020 Sub Lon less PS spectrum 2020 Urb Lon high spectrum 2020 Urb Lon mid spectrum 2020 Urb Lon less PS spectrum 2020 2022 2023 2024 2025 2026 2027 2028 2029 2030 105 5 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Small Cells Figure 1-36: Influence of varying spectrum availability on growth in cell sites for mid demand, and mid capacity (offload, spectrum efficiency) with 700 MHz in 2020 58

Millions 8 7 6 5 4 3 2 1 Rur Lincs, 2020,Less PS spec Rur Lincs, 2020,Mid Spec Rur Lincs, 2020,Hi Spec 0 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 (a) Rural Millions 16 14 12 10 8 Sub Lon, 2020,Less PS spec Sub Lon, 2020,Mid Spec Sub Lon, 2020,Hi Spec Millions 6 4 2 0 18 16 14 12 10 8 6 4 2 0 2013 2013 2014 2014 2015 2015 2016 2016 2017 2018 2019 2020 2021 2022 (b) Suburban (c) Urban 2023 Urb Lon, 2020,Less PS spec Urb Lon, 2020,Mid Spec Urb Lon, 2020,Hi Spec 2017 2018 2019 2020 2021 2022 2023 2024 2024 Figure 1-37: Influence of varying spectrum availability on growth in cell sites for mid demand, and mid capacity (offload, spectrum efficiency) with 700 MHz in 2020 2025 2025 2026 2026 2027 2027 2028 2028 2029 2029 2030 2030 59

Summary of sensitivity to public sector spectrum availability In Figure 1-39 we show the impact on the network costs of public sector spectrum becoming available more rapidly, reaching 24% of relevant spectrum ( hi ) or at a slower rate ( late pub. sect ), where it represents only 11% of spectrum in 2030. The corresponding impact on cell sites is shown in Figure 1-38. It is clear that public sector spectrum forms a significant element in overall mobile capacity and its availability and usefulness (including the impact of harmonisation) can substantially impact on the scale of network build-out and the costs of meeting future demand, especially in urban and suburban areas. No. of cell sites 800 700 600 500 400 300 200 100 0 611 447 400 132 106 98 late pub. sect. 158 292 Mid Hi late pub. sect. 75 59 37 25 25 236 231 192 192 188 Mid Hi late pub. sect. Small cells 2030 Macrocells 2030 Mid Urban Suburban Rural Hi Figure 1-38: Impact of varying the rate and quantity of public sector spectrum on cell sites (in 2030), with and without availability of (mid demand and mid capacity scenarios, 700 MHz in 2020). 25 21.7 22.5 Network costs to 2040 ( m) 20 15 10 5 0 6.2 3.2 8.4 6.8 0 0 0 late pub. sect. Mid Hi late pub. sect. Mid Hi late pub. sect. 10.8 10.5 Mid Urban Suburban Rural 9.7 Hi Figure 1-39: Impact of varying the rate and quantity of public sector spectrum on network costs (to 2040), with and without availability of (mid demand and mid capacity scenarios, 700 MHz in 2020). Costs should be treated as illustrative and relative rather than absolute. 60

1.14 Overall findings The impact of 700 MHz on the number of sites and the cumulative network costs to meet wireless broadband demand in the scenarios examined is summarised in Figure 1-40 for our mid demand, mid capacity scenarios. Given the long time period at issue here, there are very substantial uncertainties in the size and timing of both the demand for wireless services and the supply of capacity. This has been demonstrated by analysing the key sensitivities such as the timing of 700 MHz, the quantity and availability of spectrum and the level of offloaded demand. However, only the key assumptions could be modelled but there are various other assumptions that could materially impact the impact of 700 MHz, as summarised in Table 0-1 and in more detail in later chapters. Nevertheless, our study indicates the plausible ranges of these factors given current knowledge in the UK situation and provides a means of establishing the critical factors to balance demand and the supply of capacity with regard to both the scale and the cost of the necessary networks and establishes a guide to policy makers and operators as the period passes. Our key findings are summarised in Table 1-2.Overall, our study indicates clearly that both lower frequency and higher frequency spectrum have a role to play in future mobile capacity and that additional spectrum acts in combination with other sources of capacity such as small cells, offload and technology enhancements, with each approach benefiting from the presence of the others, rather than as substitutes. Saving (relative to no 700 MHz) 60% 50% 40% 30% 20% 10% 0% 21% 19% 42% 31% 28% 28% 21% 35% 52% 41% 55% 57% Network Cost saving (to 2040) New site saving (macro) New site saving (total) 22% 22% 21% 18% 15% 11% 2026 2020 2026 2020 2026 2020 Urban Suburban Rural Figure 1-40: Cost advantage of 700 MHz in mid demand, mid capacity scenarios 61

Table 1-2: Summary of key findings Issue Finding based on our analysis Commentary Demand trends Impact of technological innovation Spectrum growth Impact of 700 MHz Based on current trends and our analysis of devices and user mobility, mobile broadband is projected to grow between 23x and 297x over the period 2012-30, with 80x being our mid case scenario. While growth will be high over the period, there is potential for the growth rate to reduce in the latter stages of this period. The non-uniformity of traffic between users, locations and environments (indoors and outdoors) and times of day is a major driver of the required form of capacity enhancement. The evolution of enhanced technologies, including via LTE- Advanced and its evolutions could deliver spectrum efficiency growth to existing cell sites of between 3.3x and 10.1x between 2012 and 2030, with a mid case of 6.2x. We have analysed the associated costs and provided guidance on the relative merits of the available techniques. Beyond the award of 800 MHz and 2.6 GHz, there is scope for substantial additional availability of harmonised spectrum for wireless services, representing around 350 MHz of additional spectrum for downlink capacity. This could deliver a growth in available spectrum capacity for the downlink between 7x and 13x over the period considered. This is expected to deliver sufficient capacity for networks of approximately the current scale of macrocells out to around 2024 with our mid-case growth and capacity assumptions (which include significant growth in macrocell spectrum efficiency and the number of small cells deployed). A 700 MHz band would represent only 5 to 9% of the relevant spectrum at 2030, but yields greater benefits due to its distinctive physical properties. These produce a benefit in terms of reducing the number of additional sites by between 18% and 52% These ranges are not forecasts, but an indication of a plausible range of outcomes. Given this wide range, there is a need to secure options notably spectrum options for enhancing capacity, while making firm decisions on those options flexibly as the actual demand emerges. The inclusion of additional antennas in both base stations and mobile devices is key to achieving the higher growth rates, as is the successful adoption of advanced interference mitigation techniques supported by close coordination and low-latency backhaul between base stations. Public sector spectrum release at frequencies above 2 GHz forms a major element of future spectrum capacity, and the rate at which it becomes available, harmonised, and included in mass-market data devices could vary the rate of spectrum availability significantly. Both the coverage and the spectrum efficiency properties of 700 MHz play a role in it delivering a greater benefit than the quantity available would suggest, including in its ability to deliver reliable indoor coverage from outdoor sites. The impact of 700 MHz varies 62

Issue Finding based on our analysis Commentary Impact of outdoor small cells Impact of indoor traffic offload (depending on the area) for 700 MHz availability in 2026 in the mid scenario for demand and capacity. Network costs are also reduced by between 11% and 27%. Earlier release in 2020 could substantially increase these benefits to 21%-57% site reduction and 15% to 41% network cost reduction. If operators can overcome challenges associated with determining localised areas of high demand and acquiring suitable sites to address them, then small cells are expected to play a significant role across all the scenarios studied. Growth varies substantially by region, but for our mid scenarios outdoor small cells represent 12% (rural) to 81% (urban) of all outdoor cells with 700 MHz availability in 2026, and somewhat higher without it. Indoor offload devices, whether using Wi-Fi or femtocells approaches in licence-exempt or licenced spectrum, already offload substantial traffic (around 30-40%) from wireless networks and this use is expected to increase, perhaps to as high as 60% by 2030. However, the costs can be substantial compared with outdoor network costs when widely deployed and this could limit offload deployments to some extent. If so, network costs are increased to compensate. The availability of 700 MHz in 2020 was found to mitigate this risk, reducing network costs in our lowest offload scenario to below those of our high offload scenario in the absence of 700 MHz. substantially with geographical area, depending on the balance of coverage and capacity. Where coverage limitations dominate areas, there is a reduction in the rate at which new sites need to be built. Where capacity limitations dominate, 700 MHz delays the advent of the need to build additional sites, which can significantly affect the cost although the relative timing of the spectrum availability and the capacity crunch is critical. Outdoor small cells act to reduce the number of additional macrocell sites (and associated costs) which would otherwise be required in two ways. They act as a low cost means of providing coverage to locations where the number of individuals affected is relatively small, for example in rural areas. This also helps the macrocells to continue to deliver wide area coverage without becoming range limited due to capacity constraints. They deliver capacity to localised hotspots of demand, allowing the growing capacity of macrocells to meet the wide-area capacity needs. This applies to any area with a wide spatial variation of traffic needs, and we observe significant growth for this purpose across all our study areas. There are open questions concerning the enabling factors for offload quantities to keep up with the growth of demand, including availability of suitable backhaul, sufficiency of spectrum (whether licenced or licence-exempt) and the ability of offload devices to be targeted on the most effective locations. We recommend further study of these issues. However the uncertainties may be less when addressing some proportion of indoor demand from outdoor sites, in which case spectrum bands such as 700 MHz could yield an increased benefit. 63

2. Introduction 2.1 Scope of Study This study was conducted to support Ofcom s understanding of the techniques available to increase the capacity of wireless broadband networks over the time period 2012 2030. From the outset of this project the key drivers were to improve the understanding of: The extent to which additional spectrum (including the 800 MHz and 2600 MHz frequency bands) will meet future demand over the next 10-15 years. The role additional spectrum bands might play in meeting this demand, including the release of an additional 500 MHz of spectrum by the public sector, and the ongoing international harmonisation of the 700 MHz band and other higher frequency bands The role of additional sectors and smaller cells The role of more efficient standards such as LTE The potential for offload to Wi-Fi and/or femtocells The role of additional spectrum needed for wireless broadband backhaul capacity During the early stages of the project these drivers were used to identify an overarching question for the project to address, stated as follows: Main study question How much does the addition of 700 MHz and other harmonised spectrum bands affect the scale of the infrastructure and the cost of delivering wireless broadband in the UK using standardized mobile technologies over the period up to 2030 given: Existing mobile spectrum plus 800 MHz and 2600 MHz as a baseline Expected growth in the (spectrum and productive) efficiency of mobile technologies and topologies A range of possible scenarios for the size and nature of UK demand Note that, although our study is focused on the comparative network scale and costs of meeting demand according to the available spectrum, this is only one element of the value of additional spectrum, which may also: Enable competition Enable innovation Improve user experience by increasing the quality of services which can be economically delivered In order to fully address the main study question, we have developed a methodology to address this question as follows: 64

Demand scenarios We created demand growth scenarios for the period 2012-2030 which incorporate the highly non-uniform characteristics of mobile broadband demand by location, device, time of day and user. The demand cases were developed so that a flexible range of low, mid and high scenarios could be analysed to determine differences in capacity techniques. Capacity analysis We determined, via an automated optimisation technique, cost-efficient networks to serve the growing demand in a variety of representative areas of the UK, subject to varying assumptions regarding the efficiency of wireless broadband technology and the rate and timing of availability of suitable spectrum. Cost analysis We compared the cost of meeting demand over the entire period between scenarios and hence determine the risks and benefits of varying levels of spectrum release, especially regarding 700 MHz and higher frequency (above 1 GHz) spectrum. This report describes in detail the methodology and assumptions necessary to derive the demand and supply scenarios required to address the key objective of the study. It also presents the outcomes and findings based on a range of scenarios selected to meet Ofcom s requirements. 2.2 Related Studies There are a number of related studies that provide a variety of interesting methods, solutions and observations when examining how the growth of data traffic is likely to be addressed by mobile network. Some of the studies focus on one aspect, such as densification of sites and others focus on a mix of aspects such as available spectrum and site densification. Altogether, they present a useful insight into the challenges faced by mobile networks due to the unprecedented growth in mobile traffic predicted over the next few years. The studies below are summarised highlighting the key messages that emerge and how this relates to the present study. Nokia-Siemens Networks Nokia-Siemens conducted an investigation[ ii ] into the maximum capacity of mobile broadband solutions from the viewpoint of traffic quality versus distribution over time and location. The analysis sought to determine the cost of mobile broadband taking into account the volume of mobile data traffic per user and the number of active data subscribers per site. The solution examined the use of upgrading existing sites with more bandwidth and evolution of technology from HSPA to LTE. The study found that monthly CAPEX and OPEX can be kept below 3 EURO per subscriber over an eight year depreciation period. This was assuming that mobile broadband penetration would be at least 500 subscribers per site that used less that 2 GB per month. This work also studies the evolution of technologies and impact on the costs for end users. In a related study iii, Nokia-Siemens indicated that a growth in capacity of 1000 times could be achieved over the period 2010-2020 with equal contributions of ten times each from additional spectrum, spectrum efficiency and base station density. 65

Ericsson Research and Royal Institute of Technology (Sweden): Modelling the cost of heterogeneous wireless access networks[ iv ] This study investigated the impact heterogeneous wireless access networks have on the total infrastructure cost against non-uniform traffic distributions. The study presents a methodology used to quantify the average total cost of different system configurations for both third generation mobile systems and Wireless LAN systems. The study found that: introducing multiaccess networks was equally cost- efficient as single-access hierarchical cell structures. The study also revealed the important determinants for mobile operator deployment strategy which include the competition, time-evolving demand for traffic, differentiated area coverage, pricing strategies for different services, the availability of base station site locations and spectrum. Ericsson: Mobile broadband busting the myth of the scissor effect [ v ] The Ericsson paper investigated the costs of increasing capacity via various means, and concluded that capacity could be increased substantially at rapidly decreasing cost per unit demand, with a marginal cost of around 0.1 euro per gigabyte given high utilisation of the relevant network elements. Picochip: Estimation of the potential deployment of small cell base stations in 2015 [ vi ] This study investigated the approach to estimating a global small cell deployment in 2015 required to deliver the data capacity implied by the mobile data forecasts of Cisco VNI [ vii ] for a dense urban area. It used spectrum efficiency assumptions drawn from our own 4G Capacity gains report[ viii ]and focused on the traffic net of traffic offloaded via Wi-Fi and femtocells according to Cisco s forecasts. The study determined that around 70,000 outdoor small cells deployed by two infrastructure providers could meet the capacity needs of London in 2015 without additional spectrum. Real Wireless: 4G Capacity Gains report [ viii ] A previous study by Real Wireless on behalf of Ofcom investigated the increase in spectrum efficiency of 4G technologies compared to 3G over a ten year timeframe. It indicated that spectrum efficiency growth in the UK context was barely enough to meet the low range of analyst growth forecasts over this time frame in dense urban areas and would be insufficient on its own to meet the needs of hyperdense local areas, where additional spectrum and/or small cells would be necessary. We did not however consider the relative cost of the various solutions or the specific sources of additional spectrum. These studies and others provide useful insight and background to our study, but none fully address the combination of spectrum, technology, topology and cost issues which are crucial to address Ofcom s needs, so a more elaborate methodology was required, as described in the next chapter. 66

2.3 Report structure The report is structured as follows: Chapter 1: Introduction and Summary provides an introduction to the study, an outline of the study objectives and an overall summary of our methods and findings. It may be read as a standalone overview of the whole study. Chapter 2: Introduction describes the scope of the study, presents a number of related studies that illustrate how the mobile industry is addressing the challenges of mobile data traffic growth and the report structure. Chapter 3: Methodology and Assumptions describes the methodology and assumptions generated to create the software model inputs and the functions necessary to calculate the costs of meeting future demand. Chapter 4: Results and Analysis presents the results and analysis from the 39 scenarios that have been modelled against each of the different demand cases under investigation Chapter 5: Overall findings presents our overall findings from the analysis and describes further work that could be done to understand the impacts of using alternative inputs. A set of detailed Annexes accompanies this report and provides all the supporting information relating to each of the model inputs and the detailed results. Annex A1: Site costs describes the details of the site cost model which outlines all associated equipment costs, including upgrades to site and new site build costs for small cells and macro cells. Annex A2: Technology Considerations and Spectral Efficiency describes the approach for deriving the site spectral efficiency and how this evolves over time. It includes an outline of the technology generations and the capacity techniques used for enhancing capacity Annex A3: Spectrum Scenarios describes the details of the four spectrum scenarios used as inputs for the model. This annex provides the assumptions and justification of the quantity and timing of utilising each of the mobile frequency bands. Annex A4: Site Ranges describes the site ranges and site configurations used in the model. This annex provides the link budget parameters and assumptions, propagation models, maximum range calculations and the evolution of site ranges over time. Annex A5: Demand Assessment describes how demand is distributed across the study areas and applied in the model. This annex provides details of the assumptions and source data used to derive the growth in demand over time based on a set of individual distributions for traffic volume per device, device penetration, location of devices, traffic across different times of day, and distribution of traffic amongst users. Annex A6: Technical Model Description provides a detailed overview of how the model was designed and implemented. This annex also explains how the model works in terms of the main features of how sites serve capacity based on the combination of inputs. Annexes A7 and A8: provide all of the detailed output plots of the results from the modelling exercises. References are provided at the end of this main report and following Annexes A1-A6. 67

3. Methodology and assumptions 3.1 Overview of Modelling Framework The aim of the study is to evaluate the estimated network scale and cost saving achieved through the introduction of new spectrum for operators building networks to supply traffic demands for the UK. Our approach is to model a cost efficient decision making process which an operator could adopt to determine the most appropriate level of installation or upgrade of network infrastructure and spectrum to ensure network capacity meets traffic demands. Given the many factors to be considered in determining the required scale of network, a globally optimum solution cannot be determined, but by comparing scenarios using the same efficient methodology and benchmarking the results against current realworld networks and other studies we can provide direct insight into the relative cost impact of differing spectrum scenarios, We have used three study areas to allow costs for the UK as a whole to be extrapolated. The three study areas selected were North Lincolnshire, Central London and West London and these were chosen to represent three main geotypes: Rural, Suburban and Urban environments. Analysis of these individually shows how the benefits of new spectrum differ by geotype. Figure 3-1 shows the modelling framework, which brings together a variety of inputs into a central deployment simulator, which emulates efficient operators decision making processes. The process essentially identifies areas of un-served demand and decides the most cost effective way to serve it. The options are either installing a new site to soak up the demand, or upgrading an existing site which may already cover the demand but have insufficient capacity. Upgrades include adding more sectors or MIMO antennas, switching on new carriers in an already deployed band, or adding carriers in a new band. A detailed cost model has been developed around these options. The model compares all options and selects the one that serves the greatest demand per unit cost. Figure 3-1 Modelling Framework for Cost effective deployment to satisfy Traffic Demand 68

The deployment model requires the following inputs: Demanded traffic, characterised as a point source of evolving demand in Mbps at a particular address or a stretch of road or railway. Points are distributed in a non-uniform manner according to post-code and road/rail data, to ensure a realistic representation. The demand varies by location and increases each year during the study period at a rate specific to the scenario of interest. Demand is specific to each study area. We examine the totality of demand rather than dividing it between operators, and account for the plausible evolution of the number of operators within the network costing process. Spectrum, describes the MHz of bandwidth available each year across a number of bands identified by Real Wireless and Ofcom as potentially available for harmonisation and deployment of standardised mobile broadband technologies. The spectrum input is the same for all study areas, on the assumption that spectrum for wireless broadband is likely to be awarded on a national rather than regional basis. Individual spectrum bands are explicitly modelled, but for the purposes of defining ranges and spectral efficiencies, they are classified into one of three groups: <1GHz 1-2.1 GHz >2.1 GHz Site Spectral Efficiency captures the ability of the technology to convert MHz of spectral resource into Mbps of capacity to serve demand, in units of bits per second per Hz and on an aggregate basis across all users served. Spectral efficiency varies across a number of site configurations which the operator can chose to deploy. Sites with more sectors and MIMO antennas have higher site spectral efficiency, but cost more. Spectral efficiency improves over time as new technologies are developed and algorithms improve. It also varies depending on the geotype, carrier frequency and whether demand is indoor or outdoor. Site Ranges describe the coverage area of each site, over which demand can be soaked up. Ranges vary with carrier frequency, geo-type, and site configuration. Ranges also evolve with time, as consumers expectation for a minimum acceptable data rate increases. Counterbalancing this trend, technology improvements also increase the range at which a given rate is achievable. Ofcom is particularly interested in the period 2020-2030, the time period when 700MHz might be made available. Our study period runs from 2012 to 2030, and costs are extended out beyond this period. The operator decision-making process is based on 1 year evaluation periods. Each year the demand, capacity and site ranges are updated, and the model evaluates whether there is any unserved demand and finds the costefficient network which fully serves it. It is possible that such a network is uneconomic, and in processing the total costs we evaluate the required cost per user to indicate this eventuality. 3.2 Input scenarios to address Ofcom s questions The main aim of the study is to compare the network scales and costs of introducing spectrum at various times and rates, with one key aspect being the impact of introducing 700MHz spectrum in 2020, 2026, or not at all. This is achieved by running the deployment model with different spectrum inputs to show the 700MHz band becoming available at these different times, or never. The saving is therefore evaluated by comparing the costs with the never case. It is also of interest to explore the sensitivity of this result to the assumptions for the other inputs: demand, spectrum efficiency, or the amount of other spectrum. Sensitivity analyses are performed by creating different versions of each input file to represent the 69

different scenarios. In general there is a mid case plus a low and a high case to both bound the plausible range of the input and help explore sensitivity to the parameter. The following analyses describe the low, mid and high scenarios for each input: 1. Timing of 700MHz [2020, 2026, Never] (% cost saving achieved by normalising to the Never case) 2. Amount of other spectrum: [less, baseline, more] 3. Rate of demand growth: [flattens off, balanced, high growth] 4. Spectral efficiency improvement [limits already reached, steady improvement, innovation dividend] 5. Quantity of data offload [high, medium, low] The following sections provide an overview of the methods used to generate the different input, key assumptions used and the overall result. The full detail of each input is captured in the annexes to this report. 70

3.3 Study Areas for modelling The following study areas have been selected to be representative of urban, suburban and rural environments found in the UK: Urban - Central London incorporating: City of London, City of Westminster and Kensington and Chelsea Suburban West London incorporating: Borough of Brent, Ealing, Harrow, Hillingdon and Hounslow Rural North Lincolnshire incorporating: North Kersteven, East and West Lindsey, South Holland Boston and Lincoln The Central London study area map shown in Figure 3-2 presents the demand points for the residential and business delivery addresses and the road/rail locations distributed across the area. London is considered as reasonably representative of UK dense urban areas in general, and is an important environment in itself. The West London study area map shown in Figure 3-3 presents the demand points for the residential and business delivery addresses and the road/rail locations distributed across the area. This area represents a spread of residential and business locations and wider distribution of road and rail routes. The map shows a much less densely spread set of demand points with some open areas between them, as typical of many suburban environments. The North Lincolnshire study area map shown in Figure 3-4 presents the demand points for the residential and business delivery addresses and the road/rail locations distributed across the area. This area is intended to represent a sparsely populated area with a very wide spread of the residential and business locations and wider distribution of road and rail. The map shows a sparsely spread set of demand points with the majority of the map as open spaces. This mix of sparse spread of demand points and open spaces is used to represent the rural case. 71

KEY: Residential and business demand points Focus of study area Railway points Motorway points A/B road points Residential Addresses Business Addresses km of Road & Rail Urban London Urban 273,723 Suburban 21,085 Rural 8,356 Urban 31,794 Suburban 4,420 Rural 1,204 Motorway 0 A road 108 B road 29 Railway 10 Figure 3-2 Central London study area map showing residential and business delivery addresses and roads/rail 72

KEY: Residential and business demand points Focus of study area Railway points Motorway points A/B road points Residential Addresses Business Addresses km of Road & Rail Suburban London Urban 40,090 Suburban 395,298 Rural 38,877 Urban 31,794 Suburban 4,420 Rural 1,204 Motorway 22 A road 298 B road 73 Railway 134 Figure 3-3 West London suburban study area map showing residential and business delivery addresses and roads/rail 73

KEY: Residential and business demand points Focus of study area Railway points Motorway points A/B road points Residential Addresses Business Addresses km of Road & Rail Rural Lincolnshire Urban 22,484 Suburban 192,163 Rural 114,964 Urban 806 Suburban 9,097 Rural 9,097 Motorway 0 A road 1,104 B road 782 Railway 337 Figure 3-4 North Lincolnshire study area map showing residential and business delivery addresses and roads/rail 3.3.1 Coverage area assumptions for rural Lincolnshire The prime focus of this study is to analyse and determine the impact growth in demand for wireless broadband services has on capacity. In this case one must assume there is sufficient coverage and any additional deployment costs must satisfy the need for increased capacity. However, this is not the case in all regions of the country. There are many coverage limited areas in the UK that require further coverage enhancements in parallel to providing additional capacity. In this study we investigate urban, suburban and rural areas all with varying degrees of demand but in the case of the rural Lincolnshire there are still areas of limited or no coverage, as illustrated in Figure 3-5. 74

Figure 3-5 H3G coverage of Lincolnshire from Ofcom 3G Coverage report ix (2009) In this study we incorporated the requirement to increase coverage in parallel with delivering capacity for Rural Lincolnshire so that the results provided a more representative outcome of network deployment in rural areas. We expect coverage to be enhanced in rural areas such as Lincolnshire over the study period due to the following reason: Coverage obligations that have been placed in the soon to be awarded 800 MHz spectrum licenses. The recent (Jan 2012) proposal from DCMS x to invest 150m to improve mobile coverage and quality in areas with poor or non-existent mobile coverage. Other competitive and societal pressures to extend coverage. Figure 3-6 shows the coverage target growth assumed for Rural Lincolnshire. We assume a steady decrease in mobile not-spots of 10% per year. See xi for comparison with announced national roll-out plans from one operator. 100% 98% Target coverage 96% 94% 92% 90% 88% rw EE 86% 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Figure 3-6 Coverage target growth over time for Rural Lincolnshire (rw) compared with announced rollout plan (nationally) for one operator (EE) 2022 2023 2024 2025 2026 2027 2028 2029 2030 75

3.4 Traffic Demand Assumptions A bottom-up approach was used for modelling demand in order to take into account the set of metrics that impact distribution of demand. The following distributions have been used to build up the average demand: Volume of mobile traffic generated per device type Penetration of devices amongst population Time varying demand over a 24 hour period Location of demand indoors and outdoors Distribution of traffic amongst individuals Demand points were used to represent delivery addresses and kilometres of road and rail in each of the study areas. Therefore, the quantity of demand was dependent on the number of residential and business delivery addresses and kilometres of road and rail in each study area. Equally, the demand points were distributed according to the location of each delivery address, road and rail line in each study area thus resulting in non-uniformly distributed demand according to the geographic locations within each study area. The quantity of demand is calculated using the data found from the output of the above distributions which provides the total demand for each study area based on its population. The demand point is converted from Gigabyte/month into Megabits per second (Mbps) of demand via assumptions concerning usage patterns during the day which differ by geotype. All parameters vary over the period 2012 to 2030 at rates drawn from a combination of third-party studies and our own estimates and assumptions. Figure 3-7 illustrates the combination of processes used to derive the demand maps used in each of the study area locations. Figure 3-7 Approach to deriving non-uniform demand in Mbps across locations in each of the study areas Creating the forecast evolution of demand elements required a detailed set of assumptions to be generated based on real world source data such as that published by Cisco s Visual Networking Index [vii], Ericsson s latest mobile traffic forecast[ xii ], Analysys- Mason forecasts [ xiii ] and a variety of other industry reports. The method and assumptions are provided in detail in Annex A5. 76

3.4.1 Scenarios reflecting uncertainties in future demand A set of high level assumptions were derived to articulate the possible views of how demand may evolve over time. These assumptions have been essentially based on the different rates of increase in volumes of traffic growth and uptake of devices and can be summarised as follows: Low Case: assumes early growth in demand (2012-2015) for mobile data that flattens out, potentially due to high costs of capacity resulting in unattractive process for consumers and/or a reduction in the quality of service experienced as capacity limits are reached. Mid case: assumes demand increases beyond 2015 at a rate comparable to current trends from vendor and analyst forecasts. Traffic steadily rises up to 2020 and starts to slow down from 2020 onwards as devices reach maximum penetration and traffic consumption per device peaks. High case: assumes rapid uptake in high resolution mobile video from high definition through to 3D in 2020, driven by demand for a mobile 3D experience, high resolution video gaming etc. The demand informs the basis of the capacity model by setting the level of growth the mobile network capacity must serve. We have therefore assumed a range of demand scenarios that challenge the various capacity options and configurations operators might deploy. 3.4.2 Mobile data traffic offload Data offload techniques provide a means of transferring the data traffic that would be ordinarily generated on the cellular network, i.e. from devices that are normally connected to the cellular network, to the fixed network via a femtocell or Wi-Fi service for example. Such approaches are especially suited to offloading indoor traffic in homes, offices and public buildings. The offloaded traffic frees up capacity on the macro network layer, creating a cost effective opportunity to improve performance to other users. The quantity of offload is an important factor to consider when modelling capacity, since it is this proportion of demand which is removed from the total. Estimates from Cisco[vii] suggest that 40% of cellular traffic was offloaded in 2010 in the UK and this is expected to increase to 42% by 2015. The growth data from Cisco has informed our assumptions and applying a sigmoid function[ xiv ], shows a steady rate of increase over the time frame as illustrated in Figure 3-8. In general we apply our offloading on the basis that operators have a desire to ensure cost effective utilisation of their networks and the need to supplement their networks by offloading in areas where traffic is reaching a peak. Some insightful examples of offload are given in HSBC s Research Capacity crunch in Asia [ xv ] with comparisons between operators. We assume for the purpose of our modelling that offloaded traffic is handled on either separate licence-exempt spectrum or on spectrum which is efficiently reused from the wider network without detriment, so that it effectively reduces the traffic needing to be served on the harmonised spectrum in the wider network and can be treated implicitly rather than explicitly for the purpose of modelling. 77

% of traffic offloaded at demand locations within study area 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 High Urban/Suburban Mid Urban/Suburban Low Urban/Suburban High Rural Mid Rural Low Rural Cisco VNI 2011 Figure 3-8 Growth in offload according to Urban, suburban and rural areas More detail of the assumptions and methodology for deriving offload is presented in Annex A5. 3.4.3 Overall UK traffic growth Figure 3-9 compares the outcome of our demand model when aggregated for the whole of the UK against the scenarios produced by PA Consulting for a previous Ofcom study[ xvi ]. The growth rates across the scenarios are comparable between the two studies, although our start from a higher level reflecting our benchmarking against more recent data. 10000 Real Wireless UK demand vs. PA forecast UK PB/month 1000 100 10 rw high PA High rw mid PA Mid rw low PA Low 1 2010 2015 2020 2025 2030 Figure 3-9 Traffic comparison against PA Consulting scenarios for all of UK 78

3.5 Spectrum Spectrum is a finite and valuable resource for operators aiming to supply mobile broadband capacity. We consider the quantity of spectrum available each year in the study period across a number of bands which will potentially become available for harmonised use with standardised mobile broadband technology. 3.5.1 Net bandwidth available in each band over time Spectrum bands are considered if they are expected to be: Allocated for mobile / harmonised use Cleared/available for use in the UK Used at scale (standardised) internationally Attractive (i.e. given factors like interference from adjacent usage etc.) For each band we consider: Total MHz bandwidth for downlink transmissions in any given year, since we assume that downlink is more likely to be the limiting factor in capacity (uplink coverage is also considered). For unpaired bands, we assume 89% of the spectrum capacity is allocated to the downlink to ensure sufficient TDD downlink traffic is captured by model inputs. The net bandwidth, which takes into account guard bands, and rates of re-farming of spectrum from existing uses to broadband data services. Whether there is sufficient spectrum available to actually be usable in practice The net spectrum figure captures the precise quantity of bandwidth becoming available over time. For known bands such as the 900 MHz, 1800 MHz and 2100 MHz frequency bands, the UK Interface Requirements were used to determine the total available bandwidth available so that the quantity of re-farmed spectrum could be estimated. In other spectrum bands such as those due to be released by the Ministry of Defence through its spectrum release program (See Annex A3) we have made some high level assumptions on the quantity and timing of availability based on the factors listed above. We have confirmed the assumptions across the range of scenarios as representative of the range of plausible scenarios given current knowledge and their objectives for this study. Figure 3-10 shows the bands used in this study and the net downlink quantity in our mid spectrum scenario. Note that each band is assigned to one of three frequency groups which are used elsewhere to determine the propagation characteristics which impact both range, and spectral efficiency. 79

Frequency Band MHz Available for downlink in year 20xx Group 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Paired 700 MHz <1 GHz 40 40 40 40 40 800 MHz <1 GHz 0 0 0 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 30 900 MHz <1 GHz 0 5 10 10 10 10 10 15 20 25 30 35 35 35 35 35 35 35 35 35 35 1800 MHz 1-2.1GHz 0 0 22 22 22 22 36 46 56 66 72 72 72 72 72 72 72 72 72 72 72 2100 MHz 1-2.1GHz 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 2600 MHz >2GHz 0 0 0 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 3400 MHz - 3600 MHz (UKB) >2GHz 0 0 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 3400 MHz - 3600 MHz >2GHz 0 0 0 0 0 0 35 35 35 35 35 35 35 35 35 35 70 70 70 70 70 Unpaired 1452-1492 MHz 1-2.1GHz 0 0 0 0 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 2100 MHZ TDD (1900-1920 MHz) 1-2.1GHz 0 0 0 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 2100 MHz TDD (2010-2025 MHz) 1-2.1GHz 0 0 0 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 2300 MHz (2310-2390 MHz) >2GHz 0 0 0 0 0 36 36 36 36 36 71 71 71 71 71 71 71 71 71 71 71 2600MHz (unpaired) >2GHz 0 0 0 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 40 3600 MHz -3800 MHz (UKB) >2GHz 0 0 0 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 36 3600 MHz -3800 MHz >2GHz 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 53 53 53 53 53 53 total 60 65 102 309 344 380 429 444 459 474 521 526 526 526 526 579 654 654 654 654 654 Figure 3-10 Net downlink bandwidth available in each band over the course of the study period (baseline mid scenario) 3.5.2 Consideration of white space spectrum One particular emerging spectrum band of interest that satisfies the physical properties of ideal mobile spectrum is the spectrum currently used by white space devices. Ofcom consulted on the use of this band in late 2010 [ 2 ] to permit the use of low power devices that operate in the interleaved UHF television spectrum. However, vital constraints are required for the operation of devices in this band due to the potential interference caused to adjacent DTT channels in the UK and its neighbouring countries. We determined this band should not be considered a candidate band for mobile broadband capacity analysis and therefore not included as part of our spectrum input assumptions on the basis that: The use of mobile broadband technology, such as LTE in white space spectrum, is not included in any 3GPP roadmaps currently, although the US 700 MHz band and other variants of that band overlap the white space frequency range. However, all these variants are FDD, not TDD, and finding paired spectrum amongst the white spaces will severely limit its utility. We see little prospect of this use of LTE technology passing our criteria for harmonised, standardised spectrum and also little prospect of it being seen by the mobile industry as any form of substitute for 700 MHz. However, we note that if white space use were standardised at some point in the future and led to a sufficient ecosystem for user devices to be considered harmonised, the utility of the spectrum would inevitably be less than the same quantity of cleared sub 1GHz spectrum. 2 http://stakeholders.ofcom.org.uk/consultations/geolocation/statement/ 80

A detailed calculation of this utility is outside of the scope of this project, but we can consider two 'bounding' viewpoints: In the best case, white space could be considered to entirely replicate what could be done with licenced spectrum, including its wide area/deep in-building penetration characteristics, but at some 'discount' related to the limited geographical availability. In this case, the modelling is just the same as for an equivalent quantity of 700 MHz spectrum accounting for the discount. In the worst case, white space usage is 'only' suitable as an additional form of offload. If spectrum were a constraint on such usage then white space could increase the likelihood of higher offload scenarios, which is captured by our offload input scenarios. However we don't expect this to be the dominant constraint (other constraints include the cost and availability of suitable backhaul, the cost of devices, the cost and scalability of device management etc.) 81

3.6 Spectrum scenarios Spectrum quantities and timing are derived to represent the following scenarios: Availability of 700MHz band: 2020, 2026 or Never Quantity of >1GHz spectrum: Late PS, Less, Mid or More The availability of 700MHz scenario is of special importance to this study, as it enables calculation of the estimated cost saving achieved by making the 700MHz band available. We run the 2026 and never cases for all other analyses to ascertain the saving due to the presence of 700MHz for different demand growth or technology improvement rates for example. The quantity of >1GHz spectrum scenarios represent the total amount of bandwidth available in the higher frequency bands, which make up the majority of available spectrum, but do not share the enhanced propagation characteristics of the <1GHz bands. Less and more scenarios are defined with the aim of bounding the range of possible outcomes, and a mid case defined between these extremes. Figure 3-11 summarises the total spectrum available in all bands (including 700MHz available in 2026), for each of the three scenarios. Two lines also indicate the relative size of the 700MHz band available in 2020 and 2026. Available net downlink specttrum (MHz) 900 800 700 600 500 400 300 200 100 0 65 Total 'More' spectrum Total 'Mid' spectrum Total 'Low' spectrum Total 'late PS' spectrum Availability of 700 MHz in 2020 Availability of 700 MHz in 2026 764.1 654 424.85 411.5 Figure 3-11 Total spectrum available in each modelled scenario Annex A3 describes the method for deriving the spectrum scenarios and the detailed assumptions for the quantity and timing of introducing each frequency band across the time frame. 82

3.7 Site Ranges The maximum ranges vary according to the antenna configuration, the site type, the environment (clutter) type around the site and the frequency band. Wherever possible, the parameters and assumptions used for the calculation of site ranges are consistent with previous Ofcom studies. See Annex A4 for details. Site ranges were calculated for all combinations of the following parameters: Figure 3-12:Parameters for site range calculations Combinations of site range calculations Clutter type: Rural, Urban, Suburban Demand type: Indoor and Outdoor demand Frequencies: Sub 1GHz, 1-2.1 GHz and >2.1GHz Link direction: Uplink and Downlink Site type: a) Macro cells 3 sectors 2 antennas, b) Macro cells 3 sectors 4 antennas, c) Macro cells 3 sectors 8 antennas, d) Macro cells 6 sectors 2 antennas, e) Small cells 1-2 sectors 2-4 antennas Year: Time evolving ranges for minimum acceptable user data rate in the uplink and downlink over the period 2012-2030 The site range calculation work first involves calculation of maximum allowable path loss (MAPL) by means of link budget formulas using the list of parameters and assumptions for each site type. In the next step, the MAPL value is used with an appropriate propagation model for the site and clutter type to determine the range. The calculations follow these steps: Select a year from the range 2012-2030 For the selected year: Obtain the cell edge throughput requirements in Mbps, minimum user device bandwidth, SINR cut off values Select a combination of parameters Calculate maximum allowable path loss (MAPL) for the selected combination Using the MAPL and selected combination calculate maximum range as minimum of the associated uplink and downlink ranges Repeat for all parameter combinations While year<2031, run steps 1 and 2 Figure 3-13 below shows an example of the final site ranges for different site types operating in 700 MHz in rural areas serving outdoor demand for macro cell and small cell sites. The final site ranges are obtained from both the downlink and uplink ranges by selecting the one with minimum range for each year. It is assumed here that in the downlink, the minimum bandwidth of user devices increases over time from 5 MHz in 2012 to 40 MHz in 2030. This increase of bandwith in different years leads to improvement in downlink site ranges. It can be seen from Figure 3-13 Site ranges for different site types operating in 700 MHz in rural areas serving outdoor demands for macro cell and small cell sitesthat in year 2012, the site ranges for all macro cells are equal. In this year the limiting case from the downlink and uplink ranges has been the downlink ranges since only 5 MHz of bandwidth is available for user devices. Hence, even if the uplink ranges for macro cells 3 sectors and 8 antennas are much higher, the 83

downink ranges which are shorter, are selected as final ranges. In the year 2014, the device bandwidth increases to 10 MHz; this leads to increase in ranges forall macro cell sites. The ranges of small cell sites also evolve over time but are much lower compared with that of macro cell sites. For macro cell sites with 3 sectors and 2 antennas from 2014 the uplink ranges become limiting cases and hence the ranges decrease each year untill 2030. It can be seen that macro cells with 3 sectors and 4 antennas and 6 sectors & 2 antennas have almost the same ranges. The macro cell sites with 3 sectors and 8 antennas have the highest ranges and this is mainly due to combination of the two factors: a) minimum user device bandwith increasing in different year till 2030 and hence increasing the downlink ranges b) use of 8 antennas for the uplink also leads to significant gain in the link budget and hence the high site ranges. Eventually the uplink ranges become the limiting cases for these site types and the ranges drop from 2020 onwards. 30 25 20 Maximum range, km 15 10 5 Macrocell, 3 sectors, 2 antennas Macrocell, 3 sectors, 4 antennas Macrocell, 3 sectors, 8 antennas Macrocell, 6 sectors, 2 antennas Smallcell, 1-2 sectors, 2-4 antennas 0 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 Year Figure 3-13 Site ranges for different site types operating in 700 MHz in rural areas serving outdoor demands for macro cell and small cell sites The effects of varying site ranges over time can potentially introduce randomness into the deployment of sites. For example if one particular site does not get upgraded early in the timeframe and another one does, then the upgraded site has an advantage in terms of range from that point in time and can create an imbalance later in the timeframe. Therefore, in order to minimise potential random effects in the results we decided to set all site ranges across types to the same level. Figure 3-14 shows the site ranges across all the environments that remain static over time from 2012 through to 2030. 84

Range Variation over Environment and Frequency in 2012 25 20 15 10 5 0 In Out In Out In Out In Out In Out In Out In Out In Out In Out Urb Urb Sub Sub Rur Rur Urb Urb Sub Sub Rur Rur Urb Urb Sub Sub Rur Rur High High High High High High Med Med Med Med Med Med Low Low Low Low Low Low Macro3sec2tx 0.69 1.98 1.17 2.86 3.44 8.43 0.91 2.26 1.66 3.55 5.61 12.01 2.72 5.31 3.77 6.37 12.68 21.46 Macro3sec4tx 0.69 1.98 1.17 2.86 3.44 8.43 0.91 2.26 1.66 3.55 5.61 12.01 2.72 5.31 3.77 6.37 12.68 21.46 Macro3sec6tx 0.69 1.98 1.17 2.86 3.44 8.43 0.91 2.26 1.66 3.55 5.61 12.01 2.72 5.31 3.77 6.37 12.68 21.46 Macro6sec2tx 0.69 1.98 1.17 2.86 3.44 8.43 0.91 2.26 1.66 3.55 5.61 12.01 2.72 5.31 3.77 6.37 12.68 21.46 Small Cell 0.09 0.20 0.35 0.41 0.45 0.79 0.10 0.23 0.41 0.42 0.48 0.76 0.20 0.38 0.43 0.48 0.57 0.75 Macro3sec2tx Macro3sec4tx Macro3sec6tx Macro6sec2tx Small Cell Figure 3-14 Site range variation between environments In summary, this work has calculated site ranges for different site types, frequencies, technologies and propagation scenarios for the overall capacity modelling framework to process these inputs to meet the objectives of the project. 85

3.8 Site Spectral Efficiency A set of spectral efficiency inputs have been produced to describe the impact over the following variables: 5 site configurations (macrocell with 3 or 6 sectors, each having 2,4, or 8 antennas, or Outdoor small cell) 3 geotypes, (rural, urban, suburban) 2 demand locations (indoor/outdoor) 18 evaluation periods (2012-2030) 3 carrier frequency groups (<1GHz, 1-2.1GHz, >2.1GHz) 3 scenarios for technology evolution (low, med, high) Full details of the reference sources, assumptions and analysis are provided in Annex A2. 3.8.1 Technology Evolution: 3G-4G and beyond Over the period 2012 2030 technology will evolve from HSPA to LTE to LTE-Advanced and beyond. We do not explicitly model the operator decision to adopt or re-farm spectrum to newer generations, rather we assume that a site spectral efficiency will represent the available mix of the day. We consider spectral efficiency for 3GPP releases of HSPA, LTE release 8 [ xvii ], LTE-Advanced (release 10) [ xviii ] and project trends forwards to releases named 12, 14, 16 and 18 beyond. These efficiencies are weighted and combined according to the proportion of spectrum that is likely to be deployed with each technology over time. Figure3-15 shows the assumption here, starting with GSM and HSPA and evolving to the LTE and later releases. % Spectrum Deployed per Tech Generation 100% 80% 60% 40% 20% 0% 2030 2029 2028 2027 2026 2025 2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 LTE-A r18 LTE-A r16 LTE-A r14 LTE-A r12 LTE-A r10 LTE r8 HSPA+ HSPA R6 GSM Figure3-15: Evolving proportion of spectrum deployed with each technology generation 3.8.2 Device mix We implicitly model the increasing numbers of laptops, tablets and smartphones in the device mix, a trend which leads to increasing numbers of antennas per device over time. We weight antennas per device by the amount of traffic served. Initially all traffic is consumed by 2 antenna devices, but gradually the traffic is increasingly consumed by 4 and 8 antenna devices. We assume there will be a gradual evolution of devices over time as the capability of devices becomes a driving factor to support increased data consumption. Device development is governed by multiple standard and interface 86

technology and current devices such smartphones are now able to incorporate multiple band antennas. For example in the Samsung Galaxy S there are 6 antennas mounted in the handset 3 to support all the different RF bands featured. This also assumes that devices are capable of supporting multiple bands (>4) and will be able to support more bands in future ranging across sub 1 GHz up to above 2.1 GHz. A Real Wireless report xix recently published by Ofcom showed the current capability of mobile devices supporting up to 5 licensed frequency bands. 3.8.3 Site Configurations For macrocell sites (macrosites), site spectral efficiency increases with the number of sectors and number of antennas for MIMO. Different macrosite configurations are explicitly modelled, as each will incur different costs and thus the choice of which type to deploy (or upgrade to) will have to take into account the cost as well as the benefits (in the form of the quantity of demand served). Unlike macrosites where sectorisation and number of transmit antennas will be explicitly modelled as an upgrade option, it is assumed that small cells will be replaced rather than upgraded, and that the site spectral efficiency will represent the mix of the day. We expect to see an evolution of small cell technology from single sector only towards two sectors (which may for example point in opposite directions along a street) and from 2 antennas to 4 antennas, enabling the higher order MIMO modes. bps/hz/site 40 35 30 25 20 15 10 5 Site Spectral Efficiency Evolution for Various Configurations Mid - Steady Technology Improvement 0 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 Macro 6sec, 8tx Macro 6sec, 4tx Macro 6sec, 2tx Macro 3sec, 8tx Macro 3sec, 4tx Macro 3sec, 2tx Outdoor Sm Cell Figure 3-16: Evolving site spectral efficiencies for urban geotype, outdoor demand for 1-2.1 GHz carriers 3 http://www.antenna-theory.com/antennas/patches/pifa.php 87

3.8.4 Geotype, carrier frequencies and indoor/outdoor demand 120% Scaling of Spectral Efficiency for Geotype, Carrier Frequency and Indoor/outdoor Consumers 100% 80% 60% 40% 20% 0% Sub Lon Urb Lon Rur Berks Rur Lincs Outdoor 800 MHz Indoor 800 MHz Outdoor 1800 MHz Indoor 1800 MHz Outdoor 2600 MHz Indoor 2600 MHz Figure 3-17: Figure Scaling of Urban outdoor 1800MHz results to other environments The site spectral efficiency evolution figures for urban outdoor 1-2.1 GHz shown in Figure 3-16 are scaled by the factors in Figure 3-17 to represent other environments. The factors are the result of a detailed coverage and capacity study. 3.8.5 Scenarios In order to represent a range of possible evolution scenarios for standardised mobile broadband technology, we consider three possibilities: Little further growth (low) assumes that current day mobile broadband technology is already approaching the limits of what is achievable in terms of site spectral efficiency. Steady Growth (mid) represents a steady improvement in site spectral efficiency, as algorithms improve and new techniques are introduced to co-ordinate and reduce the interference which ultimately limits cell throughput. Innovation dividend (high) represents a significant leap forward in the spectral efficiency mobile broadband technologies. Although we cannot specify exactly how this will come about, the actual efficiencies figures will be based on a significant improvement over the steady growth case The scenarios proposed for this study generally does align with our previous 4G Capacity Gains report in that a 3 sector two transmit antenna cell spectral efficiency for our mid case up to 2014 aligns closely. In 2020 the cell spectral efficiency is 1.71 bps/hz for this study compared to 1.28bps/Hz from the 4G Capacity Gains report as shown in Figure 3-18. 88

Cell SE, bps/hz/cell 3.00 2.50 2.00 1.50 1.00 0.50 Cell Spectral Efficiency Comparison Capacity Techniques Macro 2Tx med 4G Cap Gains: 2G+3G+4G combined 1.71 1.28 0.00 Dec-10 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 Dec-18 Dec-19 Dec-20 Dec-21 Dec-22 Dec-23 Dec-24 Dec-25 Dec-26 Dec-27 Dec-28 Dec-29 Dec-30 Figure 3-18: Cell spectral efficiency comparison between this study and our 4G Capacity Gains report The purpose of the scenarios is to model a spread of technology improvement which can help us understand the sensitivity of our findings to our assumptions in this area. This also enables us to bound the plausible rates of technology improvement. The scenarios impact the choice of spectral efficiency figures and growth beyond release 10 (LTE-Advanced) for which industry wide simulation results are available. 3.9 Site Costs This section sets out an overview of the approach and assumptions we use to estimate costs inputs for the technical or study area models and for our overall cost benefit assessment. The details of the costs and sources used are provided in Annex A1. 3.9.1 Outline of the costs estimated We look at network costs only and do not cover retail costs. This is because retail costs are unlikely to vary significantly with the choices for increasing network capacity that are the main focus of this study. The costs we estimate comprise: Annual operating costs Capital expenditure for new equipment Capital expenditure for replacement investment. We estimate current costs 4 and project forward in subsequent years by applying annual cost trends. For replacement investment, we model a replacement cycle. Each replacement will incur a cost which will be the capital expenditure cost of a new unit of equipment in the year of replacement. 4 Most of the starting cost data are estimated for 2011 and then converted to 2012, the start of the model period, by applying a cost trend, some costs are estimated for 2012. 89

3.9.2 Modelling timeframe Since the study area models runs over the period 2012-2030, the full impact of changes that happen towards the end of the period may not be captured in a cost model covering this period - some elements of expenditure may be long term, e.g. 30 years for some site build costs. Therefore, we extend the cost model for an additional 10 years (to 2040) to counter this bias against techniques introduced late in the model period, but only measuring the on-going costs of the existing network beyond 2030. 3.9.3 Cost inputs for the technical model The main capacity enhancing techniques that we explicitly model comprise a number of macrocell related costs, including upgrades to macrocell technology, the deployment of outdoor small cells and the deployment of additional spectrum bands. For macrocells and outdoor small cells, we identify the type and number of equipment components necessary to implement that technique in order to estimate the total cost per site. This total cost per site feeds into the technical model and enables it to calculate the optimal technology to deploy in each modelling period, i.e. the lowest cost way of meeting capacity demand. There are two exceptions to this: First, indoor smaller cells are modelled through their impact on demand i.e. demand is off-loaded from the public mobile network. However, there is still a cost to deploying indoor small cells, hence we calculate this separately from the cost of the public network. Second, although we input the cost of upgrading existing macrocell sites to carry new spectrum bands to the technical model, we do not input the cost of acquiring new spectrum. Spectrum costs are added back in once we have run the technical model. We treat spectrum in this way because operators base their decisions to buy spectrum over a long time period, say 15 to 20 years which does not fit well with the 12 month decision period of the technical model. Figure 3-19 below shows the capacity enhancing techniques we model in relation to macrocells. It shows that we model new build sites and upgrades to existing sites. It also explains that we do not model the costs for techniques such as Carrier Aggregation which, as explained in section 3.8 above, we treat as implicit changes to the network. Basis for macrocell densification Higher order MIMO Increased sectorisation New build A -3 sector 2Tx MIMO B -3 sector 4Tx MIMO C -3 sector 8Tx MIMO D -6 sector 2Tx MIMO Explicit technology upgrade From A to B Antennas, cabling, civil works From B to C Antennas, cabling, civil works From A to D Antennas, cabling, civil works Implicit technology upgrades 3G to LTE we assume multi-standard base stations deployed so costs is already accounted for Future 3GPP Releases, Carrier aggregation etc. we assume spread into network by natural replacement cycle, hence cost is implicit Adding spectrum bands Explicit costs incurred base station equipment, antennas, civil works etc. when a new band or bands cannot be accommodated by existing configuration an upgrade will be required for all sites where extra capacity is needed Figure 3-19: Overview of cost calculations relating to macrocells 90

3.9.4 We estimate the costs to society Our default position is to assess costs to society. This means that we use a social rather than an operator discount rate when calculating the present value of costs (and benefits) in our scenarios. This fits in with a regulatory perspective which is interested in the costs (and benefits) to society of decisions that could impact on wireless broadband capacity. However, we recognise that operators decisions do not take into account the wider costs to society so we carried out limited sensitivity checks using a commercial discount rate instead of a social discount rate. 3.9.5 Main cost estimates Figure 3-20 below summarises the main cost estimates for macrocell densification, higher order MIMO, increased sectorisation, outdoor small cells and adding spectrum bands to existing cells that drive the choices in the technical model. Figure 3-20: Main cost inputs for the technical model (present value at 2012) medium estimates 91

4. Results and analysis 4.1 Introduction The results presented in this chapter demonstrate how introducing 700 MHz spectrum into a mobile network can generate cost savings of up to 28% when deployed at different times over the 18 year project time frame. This cost saving is based on minimising the requirement to deploy additional sites to meet the growth in demand. In order to interpret the results we first illustrate how the quantity of 700 MHz spectrum, with respect to total available spectrum, and the physical properties of the band can impact on the potential cost saving. We then present the results from 39 scenarios that reveal how the timing of 700 MHz impacts on the cost savings for mid demand and also how the high demand, low capacity case and low demand, high capacity case affects the utilisation of 700 MHz and ultimately any cost saving that might be realised. The results annexes A7 and A8 provides the raw output result plots for each of the scenarios, out of which, a selection have been used in this chapter to illustrate the cost savings of 700 MHz. 4.1.1 Quantity of 700 MHz as a proportion of total available spectrum We have assumed that 40 MHz downlink bandwidth becomes available in the 700 MHz band for use at two dates in the future, 2020 and 2026. The proportion of 700 MHz spectrum against the total available mobile spectrum is shown in Figure 4-1 and Figure 4-2 below for the low, mid and high spectrum scenarios. It can be seen that 700 MHz at a minimum is 5% of the total available spectrum and at a maximum 9% of the total available spectrum. Having established the quantity of 700 MHz against the total available spectrum means we can measure this against the potential cost savings the introduction of this band could deliver. 700 MHz as a percentage of total spectrum (2020) 45% 40% 35% 38% 30% 25% 20% 15% 10% 5% 9% 6% 5% 0% 2010 2015 2020 2025 2030 2035 % Total Low % Total Mid % Total High % of < 1 GHz Figure 4-1 Proportion of 700 MHz against total available spectrum from 2020 over time for each scenario 92

700 MHz as a percentage of total spectrum (2026) 40% 38% 35% 30% 25% 20% 15% 10% 5% 9% 6% 5% 0% 2010 2015 2020 2025 2030 2035 Figure 4-2 Proportion of 700 MHz against total available spectrum from 2026 over time for each scenario 4.1.2 Site range advantage from sub 1 GHz spectrum % Total Low % Total Mid % Total High % of < 1 GHz A description of the physical properties of 700 MHz was captured as part of the inputs to the software model. We now use the site ranges as a method to determine the potential quality of service that could be delivered to consumers using this band at both indoor and outdoor locations. The bar plots in Figure 4-3 show how the site ranges differ between three distinct frequency bands, 800 MHz, 1800 MHz and 2600 MHz. Each band falls within the sub 1 GHz, 1-2.1 GHz and above 1 GHz categories to illustrate the contrast in site ranges for those bands. 25 Site ranges for Geotype, Carrier Frequency and Indoor/outdoor Consumers km 20 15 10 5 Outdoor 800 MHz Indoor 800 MHz Outdoor 1800 MHz Indoor 1800 MHz Outdoor 2600 MHz Indoor 2600 MHz 0 Suburban Urban Rural Figure 4-3 Site ranges across geotype and frequency band for indoor and outdoor locations 93

The sub 1 GHz spectrum clearly provides the greatest ranges for both outdoor and indoor locations with rural geotype benefitting most from the properties of the spectrum. Comparing the site ranges across frequency bands both 1800 MHz and 2600 MHz do not exceed much beyond 5 km even for outdoor locations. This means that the quality of service delivered to consumers by sub 1 GHz spectrum exceeds that of the 1-2.1 GHz bands and above 2.1 GHz to both indoor and outdoor locations. Therefore, 700 MHz will benefit consumers in all geotype locations. 4.1.3 Spectral efficiency advantage from Sub 1 GHz The other mechanism that can deliver an advantage to 700 MHz is the spectral efficiency which provides a set level of quality of service delivered to users within the cell depending on frequency and location. Figure 4-4 gives a comparison of the spectral efficiency across the three frequency bands that represent the sub 1 GHz, 1-2.1 GHz and above 2.1 GHz bands and their differences across each study area. The benefits of spectral efficiency are seen mostly in the urban and suburban areas since there is a smaller difference between indoor and outdoor locations. Whereas in rural Lincolnshire the margins between indoor and outdoor are wider and therefore the benefits of sub 1 GHz are more pronounced. 120% Scaling of Spectral Efficiency for Geotype, Carrier Frequency and Indoor/outdoor Consumers 100% 80% 60% 40% 20% 0% Sub Lon Urb Lon Rur Lincs Outdoor 800 MHz Indoor 800 MHz Outdoor 1800 MHz Indoor 1800 MHz Outdoor 2600 MHz Indoor 2600 MHz Figure 4-4 Environmental scaling of spectral efficiency for geotype, carrier frequency and indoor and outdoor locations 4.2 High level capacity analysis and the need for site densification The following section addresses the impact of demand on capacity at a high level by taking our three demand scenarios and mapping the capacity on top of them. This analysis demonstrates how the mix of capacity techniques, spectrum and spectral efficiency are combined to give an overall level of capacity that can meet one or more of the demand growth scenarios. We start the analysis by establishing the level of demand growth which is discussed in detail in section 3.4 and presented as a set of demand scenarios across each of the study areas. The growth in demand varies widely across this range based on the population differences across the study areas and the low, mid and high growth assumptions. The urban high scenario has the highest demand out of all the scenarios shown and we expect this scenario to require the greatest capacity. 94

Figure 4-5 Range of demand scenarios or each of the study areas The next step is to quantify the components of supply which are spectrum and technology. These capacity components have been discussed in detail in sections 3.5 and 3.8 respectively to illustrate the varying quantities in terms of MHz and bps/hz that can serve the growing demand. The charts in Figure 4-6 and Figure 4-7 show the spread of available capacity in each of the low mid and high scenarios. The quantity of available spectrum, increasing over time, represents a plausible range of the mix of mobile bands likely to be available across the time frame and that could be deployed by operators to serve capacity. The quantity of site spectral efficiency represents a plausible spread of capacity and technology evolution likely to become available over the project time frame with some technologies such as LTE-Advanced able to meet the low case spectral efficiency in 2030 using today s solutions. Figure 4-6 Range of spectrum scenarios for the urban and suburban study areas 95

Figure 4-7 Range of site spectral efficiency across the low, mid and high scenarios The combined available capacity is calculated by multiplying the spectrum and spectral efficiency together to give an overall capacity value in Mbps. We can illustrate how capacity maps on to demand by normalising growth from 2012 to give the relative growth for each demand case on to the same chart as shown in Figure 4-8. Figure 4-8Mapping capacity on to demand for low, mid and high cases of demand The left-hand plot in Figure 4-8 shows the high demand, low capacity case for the urban study area where demand outstrips supply by a very large margin out to 2030. The red line is the available capacity level which reaches a maximum of 20x growth from 2012 compared to 220x growth from 2012 for demand. This case would require supplementary capacity such as extra sites to meet the demand growth as all other capacity techniques are exhausted. The middle plot in Figure 4-8 shows the mid case for the urban study area which shows capacity exceeding supply for the first ten years of the time frame after which supply and demand tend to follow the same trend with some overlapping points until 2028 when demand begins to outstrip supply. This case would require a much lower number of extra sites compared to the high case. A steady increment of sites over the first ten years would be required to meet the demand in each year, with spectrum and technology combined providing the balance of capacity supply. The right-hand plot in Figure 4-8 shows the low demand, high capacity case for the urban study area where the capacity outstrips demand by a large margin out to 2030. The capacity reaches 120x growth from 2012 compared to demand which reaches only 20x growth from 2012. This means spectrum and technology on its own is capable of meeting the demand with no requirement for extra sites. Based on the analysis given above we can determine the number of sites required using the urban mid case as an exemplar by dividing the demand by the capacity. Figure 4-10 96

shows the number of sites needed to supply capacity over the project time frame and also how the introduction of 700 MHz in 2020 and 2026 has an impact on it. It can be seen that the number of sites starts in 2012 with 240 sites to meet demand in the urban study area, by 2013 the number of sites needed is greatly reduced. This is based on a 3x increase in spectrum in 2013 driven mainly by the availability of 800 MHz and 2.6 GHz on to the market. Although the sites are already built they are used to provide the capacity and coverage necessary for the next 11 years (to 2024) by which time more sites will be needed. The chart also shows how introducing 700 MHz in 2020 prolongs the amount of time the capacity can serve demand without needing more sites until around 2028. This can be compared to the 2026 line where sites are needed earlier indicating the advantage introducing new spectrum earlier can offer. Figure 4-9 Number of sites need to supply capacity in the urban mid case Figure 4-10 presents the number of sites needed for the urban study area across all of the low, mid and high cases to compare against the cases where sites are needed or not. It can be seen that in the high demand case there is only 3 years elapsed time where sites are not needed. This is because the capacity (spectrum and technology) alone is not sufficient to serve the demand and runs out relatively quickly and by 2015 more sites are needed. It is also noted that over 3000 sites will be needed by 2030 to meet this demand which could be deemed impractical in reality. In contrast, the low demand case shows there is so much capacity, that no additional sites are needed and spectrum and technology alone can serve the rate of demand growth over the time frame. 97

Figure 4-10 Sites needed to supply capacity for urban study area across all low, mid and high cases A further comparison can be made between the urban study area and the rural study area to capture the capacity limitation differences and total number of sites needed to meet demand. Figure 4-11 shows the number of sites needed to supply capacity for the rural area. The behaviour in between the low, mid and high cases is very similar to that of the urban study area. However, in rural it can be seen that fewer sites are needed in 2012, around 70 compared to 240 in the urban study area this is due to the lower demand density (and capacity limited) in rural areas compared to the urban area and therefore fewer initial sites to meet that level of demand. In the high case for rural by 2030 there are still around 1000 sites needed to meet the demand. Figure 4-11 Sites needed to supply capacity for rural study area across all low, mid and high cases In summary, the high level analysis has shown how dividing demand by potential site capacity gives the number of sites needed across each of the low, mid and high cases of demand. It suggests that given the 3x increase in spectrum in 2013 reduces the number of sites needed, and postpones further densification and thus cost of network roll out. 98

More specifically it shows that: High demand, low capacity: Require no new sites until 2015 Mid case: Requires no new sites until 2024-2028 Low demand, high capacity: No densification needed It should be noted that the capacity analysis does not consider coverage or the special qualities of <1GHz spectrum, so only the quantity of the 700MHz spectrum matters which we have assumed as 40MHz bandwidth resulting in 5-9% of total spectrum. The next section addresses the details of the results which incorporated the complexity of site upgrade configurations, spectrum band upgrade configurations and new site builds. In principle we should see the results follow the trend of the high level analysis. 99

4.3 Results from timing and availability of 700MHz This section interprets the modelled outputs and provides an explanation against the findings for the first 21 scenarios that have been run through the model. A summary table as shown in Figure 4-12 provides the details of the inputs used for each scenario, specifying the low, mid and high cases. Scenarios where all inputs are mid case represent, mid demand, mid spectrum, mid technology and mid offload. High demand scenarios represent, high demand/low offload, low spectrum and low technology and low demand scenarios represent, low demand/high offload, high spectrum and high technology. In each of these cases we introduce 700 MHz in 2026 or not at all. The exception is in the mid case which analysed the timing of 700 MHz which investigated the introduction of 700 MHz in 2020. 4.3.1 Explanation of our cost terminology The results shown in the summary table consist of number of sites (macro and small cell), cumulative cost to 2030 and to 2040, saving from using 700 MHz, the offload cost to 2030 and 2040, the spectrum costs and the monthly cost per user. All the costs are calculated as 2012 present values, using a social discount rate of 3.5% as recommended by HM Treasury xx for appraising costs and benefits to society. We calculate cumulative network cost as the sum of the incremental costs of meeting capacity. Hence we only include costs which are incurred from 2013 onwards and not any of the costs of existing equipment deployed up to and including 2012. We calculate offload costs similarly as the sum of the incremental costs from 2013 onwards of indoor small cells supporting offload traffic. Some of the offload devices may represent devices that have already been purchased, and it could be argued that these costs are not truly incremental and should not be considered. Hence, our estimate of offload costs can be seen as an upper estimate. It was difficult to produce a reliable estimate of the number of offload devices deployed specifically to meet capacity, because the extent to which dedicated offload devices will be used depends partly on operators strategy for supporting the rollout of such devices, which is very uncertain. Spectrum costs are the sum of the potential costs of acquiring all the bands used in each scenario. We estimate these costs on the basis of today s prevailing market prices for spectrum, even though the value of spectrum may change in the future because as more mobile spectrum becomes available and because of the advent of techniques which improve spectral efficiency and reduce the cost of alternatives to spectrum. We would therefore expect the spectrum costs to be upper estimates of the potential value of spectrum. We do not include the cost of spectrum already used for mobile communications or in the process of being awarded and expected to be used for mobile communications i.e. 800MHz, 900MHz, 1800MHz, 2.1GHz and 2.6GHz. This is because existing spectrum costs are sunk and we are focusing on the use of resources incremental to the current situation. We calculate total costs as the sum of the incremental network and offload costs. We have not included spectrum costs in this total, although we show them separately as it is arguable whether the cost to society should reflect them. From one perspective, it is only the opportunity cost of the spectrum that matters. In which case, it is better to consider only network and offload costs and compare the impact of say 700MHz on these costs with the value of 700MHz in alternative uses. An alternative view is that operators have to pay for spectrum and this affects their choice of capacity enhancing techniques, so it would be relevant to include spectrum costs (although a commercial discount rate is more relevant if we were taking an operator perspective). 100

Our affordability check or willingness to pay (WTP) comparison looks at the affordability of the incremental costs of meeting capacity. We calculate an equivalent monthly cost by taking the average monthly cost in each year from 2013 to 2030. Currently users spend between 10-15 a month on average for mobile communications (depending on whether mobile data/broadband/communications is the measure). Network costs represent some 50-60% of revenues so the 10-15 monthly revenue must be adjusted by this percentage. Costs are in present value terms hence the monthly revenue must be adjusted to take account of the extent to which costs are discounted. If we took an average of the present value of 1 discounted at our social discount rate of 3.5% from 2013 to 2030 it would be worth just under 75% of the initial value. Hence we have to apply this factor to the monthly revenue too. This gives a range of roughly 4 to 6 a month against which the monthly cost we calculate should be compared. An equivalent monthly cost of 0.50 would represent an 8.3% to 12.5% increase on what consumers currently pay. This is significant, but it is plausible that consumers might be willing to pay this amount more in return for faster download speeds and greater capacity. An equivalent monthly cost of 1 would represent a 17% to 25% increase on what consumers pay today and it may begin to stretch credibility that consumers would be willing to pay this much extra. It might be more profitable for operators to restrain demand by raising prices and to curtail their network expenditure. In terms of the scenario results, the incremental monthly costs implied by our cost estimates were relatively low in most cases: 0.20 / month or less, (network and offload costs); 0.05 / month or less (network costs only). So on this basis, we would conclude that the costs estimated for these scenarios are likely to be affordable. However, in the high demand scenarios, the incremental monthly costs implied by our cost estimates were significantly higher. In the Suburban London study area, the implied incremental monthly cost was 0.99 / month, (network and offload costs), 0.84 / month (network costs only). This would suggest that the cost estimates for this scenarios are unlikely to be affordable. The equivalent figure for the Urban London study area is lower at 0.51 / month (network and offload costs), 0.44 / month (network costs only) still on the borderline of affordability. For the Rural Lincolnshire study area, the implied monthly costs lie in between those for Suburban and Urban London 101

4.3.2 Cost results Area Inputs 700MHz saving for different areas 700MHz Macro sites Small cell sites Site savings 2030 Cumulative Cost, M Saving of 700MHz Offload Cost, M Spectrum Monthly from in 2012 in 2030 in 2012 in 2030 Macro Small Total to 2030 to 2040 to 2030 to 2040 to 2030 to 2040 cost, M cost/user, 1 Rural All Mid 2026 157 192 7 27 22% 9% 18% 8.231 11.022 7.5% 10.6% 25.330 33.385 21.771 0.051 33.561 44.407 2 Rural All Mid Never 157 202 7 29 - - - 8.895 12.333 0.0% 0.0% 25.330 33.385 94.435 0.055 34.225 45.719 3 Urban All Mid 2026 95 108 360 426 19% 45% 42% 4.673 6.827 13.5% 20.7% 24.432 32.241 52.511 0.012 29.105 39.067 4 Urban All Mid Never 95 111 360 481 - - - 5.403 8.614 0.0% 0.0% 24.432 32.241 23.025 0.014 29.836 40.854 5 Suburban All Mid 2026 227 240 10 80 35% 54% 52% 8.627 11.148 13.3% 21.4% 41.146 54.207 41.290 0.028 49.773 65.355 6 Suburban All Mid Never 227 247 10 162 - - - 9.953 14.181 0.0% 0.0% 41.146 54.207 18.025 0.033 51.099 68.387 Impact of 700MHz timing 7 Urban All Mid 2020 95 106 360 447 31% 28% 28% 3.923 6.224 27.4% 27.7% 24.432 32.241 67.580 0.010 28.355 38.465 8 Rural All Mid 2020 157 192 7 25 22% 18% 21% 7.771 10.518 12.6% 14.7% 25.330 33.385 28.071 0.048 33.101 43.904 9 Suburban All Mid 2020 227 236 10 75 55% 57% 57% 6.333 8.388 36.4% 40.8% 41.146 54.207 53.180 0.021 47.479 62.595 High demand cases 10 Urban High demand low cap 2026 95 179 360 5126-1.2% 5.9% 5.8% 167.951 249.713 2.4% 3.5% 22.754 29.431 37.071 0.430 190.705 279.144 11 Urban High demand low cap Never 95 178 360 5425 - - - 172.072 258.679 0.0% 0.0% 22.754 29.431 7.586 0.440 194.827 288.110 12 Rural High demand low cap 2026 157 931 7 339 15% 27% 19% 82.043 135.734 10.6% 12.7% 23.451 30.452 15.499 0.496 105.494 166.186 13 Rural High demand low cap Never 157 1068 7 462 - - - 91.771 155.498 0.0% 0.0% 23.451 30.452 31.714 0.554 115.223 185.950 14 Suburban High demand low cap 2026 227 1381 10 3934 1.6% 14.8% 12.1% 253.511 409.660 3.6% 4.9% 38.052 49.414 29.250 0.814 291.563 459.074 15 Suburban High demand low cap Never 227 1400 10 4616 - - - 262.984 430.815 0.0% 0.0% 38.052 49.414 5.985 0.844 301.035 480.229 Low demand cases 16 Urban Low demand high cap 2026 95 95 360 361 0% 0% 0% 0.260 0.290 0.0% 0.0% 28.662 38.792 20.803 0.001 28.923 39.082 17 Urban Low demand high cap Never 95 95 360 361 - - - 0.260 0.290 0.0% 0.0% 28.662 38.792 20.803 0.001 28.923 39.082 18 Rural Low demand high cap 2026 157 168 7 15 0% 0% 0% 2.430 3.322 0.0% 0.0% 30.345 41.109 16.334 0.015 32.774 44.431 19 Rural Low demand high cap Never 157 168 7 15 - - - 2.430 3.322 0.0% 0.0% 30.345 41.109 4.007 0.015 32.774 44.431 20 Suburban Low demand high cap 2026 227 227 10 10 0% 0% 0% 0.784 0.843 0.0% 0.0% 49.462 66.955 6.564 0.003 50.246 67.798 21 Suburban Low demand high cap Never 227 227 10 10 - - - 0.784 0.843 0.0% 0.0% 49.462 66.955 6.564 0.003 50.246 67.798 Network & offload M to 2030 Total cost Network & offload M to 2040 Red figures ended in 2027 Figure 4-12 Summary results table of first 21 scenarios 102

The cost results summary table shown in Figure 4-12 provides figures and numbers against each of the 21 scenarios including: Total number of macro sites and small cells required in 2012 and 2030 The percentage in terms of site savings for macros, small cells and total sites The cumulative cost in million GBP in 2030 and in 2040 The percentage cost savings in 2030 and 2040 The offload costs in 2030 and 2040 Spectrum costs The willingness to pay costs by consumers (monthly) Total network costs in 2030 and 2040 The network cost savings are used to represent the impact of introducing 700 MHz and what savings can be delivered depending on the timing of introduction. The offload, spectrum and willingness to pay costs can be used to compare against the network costs, however, we see that in most cases the offload and spectrum costs are greater than the network costs. We recognise the results potentially show a big opportunity to save on offload costs by spending more on the network with the potential for greater benefit. Conversely, there is a risk that people may not be willing to pay for the offload costs, which would increase the emphasis and importance of the network spend. 103

4.3.3 Summary of costs across scenarios and study areas We compare the relative network costs between each of the scenarios and across study areas to determine where the costs of introducing 700 MHz differ between each. Figure 4-13 shows a summary of each of the study areas for each of the low, mid and high cases and the timing of introducing 700 MHz 5. Millions 10 9 8 7 6 5 4 3 2 1 0 2013 High demand 2014 2015 2016 2017 2018 Mid demand Low demand Rural Lincolnshire Low/Mid demand 2019 Rur Lincs, 2026 Rur Lincs, Never Rur Lincs, 2020 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Millions 100 90 80 70 60 50 40 30 20 10 0 2013 2014 2015 2016 Rur Lincs, 2026 Rur Lincs, Never Rur Lincs, 2020 2017 2018 2019 Mid and low demand curves 2020 High demand Rural Lincolnshire High demand 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Millions 10 9 8 7 6 5 4 3 2 1 0 2013 2014 2015 High demand 2016 2017 2018 Sub Lon, 2026 Sub Lon, Never Mid demand Sub Lon, 2020 Low demand Suburban London Low/Mid demand 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Millions 300 250 200 150 100 50 0 2013 2014 2015 2016 Sub Lon, 2026 Sub Lon, Never Sub Lon, 2020 2017 2018 2019 2020 High demand Mid and low demand curves Suburban London High demand 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Millions 6.0 5.0 High demand Urb Lon, 2026 4.0 Mid demand Urb Lon, Never 3.0 Urb Lon, 2020 2.0 1.0 Low demand 0.0 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Millions 180 160 140 120 100 80 60 40 20 0 2013 2014 2015 2016 Urb Lon, 2026 Urb Lon, Never Urb Lon, 2020 2017 2018 2019 2020 2021 2022 High demand Mid and low demand curves 2023 2024 2025 2026 2027 2028 2029 2030 Urban London Low/Mid demand Figure 4-13 Network cost summary for each scenario across all regions Urban London High demand A key finding from running the scenarios across each of the study areas has shown by introducing 700 MHz alone offers a cost saving. In the case of timing, such as mid-2026, the cost saving is most pronounced in the suburban study area (21.7%) due to the delay in the capacity crunch by introducing 700 MHz. A larger saving is made in the mid-2020 case (40.8%) due to the earlier release of 700 MHz delaying the capacity crunch further and thus additional saving on network build out costs. 5 Note the left-hand column shows the same results as the right-hand column, but with the y-acis rescaled to better show the high demand cases 104

Comparing the urban mid case against the suburban mid case we would expect similar cost savings due to the similar demand profiles. It can be seen in the 2026 case cost savings in suburban and urban case are broadly the same. This is due to similar build out profiles of small cells after 700 MHz has been released thus resulting in similar the cost savings. Although the Rural mid case has the lowest relative cost savings compared to urban and suburban cases, the savings are still greater than the proportion of total available spectrum offered by 700 MHz and also deliver both coverage improvement and capacity improvement. 4.3.4 Timing of 700 MHz mid case scenario We analyse the timing of introducing 700MHz spectrum taking the mid case scenario results 1-9 as the data for analysis. We focus specifically on scenarios 3, 4 and 7 for the urban study area as an example. This is because introducing 700 MHz has the highest demand to serve and a very challenging capacity environment in this study area compared to suburban and rural. The following figures provide details of the site evolution, which is the number of sites required including upgrades for both macro sites and small cells and also plots for the cost advantage in each case. Figure 4-14shows the site evolution over the project time frame which consists of increase in the number of sites for both macros and small cells but also site upgrades. A site configuration for urban and suburban can start in 2012 as either a 3 sector 2 transmit antenna macro or a 6 sector 2 transmit antenna macro. In rural Lincolnshire the site configuration in 2012 was limited to 3 sector 2 transmit antenna since it is more likely this configuration type will be deployed in rural areas. Sites can be upgraded to a 3 sector 4 or 8 antenna macro in addition to a 6 sector 2 antenna macro. Section 3.8 highlights how each configuration enhances capacity. However, it can be seen from Figure 4-14 that 6 sector 2 antenna macros are the configuration types mostly deployed in this scenario. There is an increase in the number of small cells from 2021 to 2024 and small increase from 2029 to 2030 but the impact of introducing 700 MHz can be seen in 2026 since there is a limited need to build more sites in the latter part of the timeframe compared to the never case as shown in Figure 4-15. 105

600 500 Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas 400 Number of sites 300 360 360 360 360 360 360 360 360 360 360 364 376 393 397 397 397 397 402 426 200 100 95 95 95 95 95 95 95 95 95 95 95 98 102 103 103 103 103 103 107 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-14 Total number of sites for mid case urban London study area (Scenario 3) 2026 Figure 4-15 shows the case where no 700 MHz is utilised and comparing against scenario 3, there is a continued need to increase the number of sites due to alternative capacity enhancements being exhausted or not cost optimal. The comparison between scenario 3 and scenario 4 clearly illustrates how the introduction of 700 MHz delays the densification and need for further upgrades within the timeframe. 700 Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas 600 Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas 500 Macro, 3 sector, 2 antennas Number of sites 400 300 360 360 360 360 360 360 360 360 360 360 364 376 393 397 397 416 432 453 481 200 100 95 95 95 95 95 95 95 95 95 95 95 98 102 103 103 103 106 108 110 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-15 Total number of sites for mid case urban London area (Scenario 4) no 700 MHz Figure 4-16 shows the case where 700 MHz is introduced in 2020 and comparing against scenario 3 (2026), shows there is no need for site upgrades and the requirement for more small cells is much reduced and more spread out across the time frame from 2024 onwards thus delaying the need for new sites. The introduction of 700 MHz earlier in the timeframe reduces the requirement for new sites and ultimately save more on network costs compared to 2026 (Scenario 3) through to 2030. 106

600 500 Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas 400 Number of sites 300 360 360 360 360 360 360 360 360 360 360 360 360 370 370 375 384 398 419 447 200 100 95 95 95 95 95 95 95 95 95 95 95 95 98 98 98 98 100 102 105 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-16 Total number of sites for mid case urban London study area (Scenario 7) 2020 Figure 4-17 shows how the number of sites evolves over time for each of the study areas and within each, how the number of sites varies according to when 700 MHz is introduced in either 2020 or 2026. The advantage of introducing 700 MHz earlier in the time frame can be seen from the plots with the dashed lines showing the different timings. The never case requires the highest number of sites by 2030 in all regions. We see the impact of the capacity crunch in the urban and suburban study areas from the sudden increase in site builds when the networks begin to run out of capacity from site upgrades and extra bandwidth. In rural Lincolnshire there is a more steady growth in site builds which is due to the requirement for the provision of coverage. This can be seen from year 2017 where the number of macro sites begins to increase in all three timing scenarios. The urban and suburban areas show the impact of a capacity crunch. In suburban the demand is more uniformly spread with macro sites and small cells satisfying demand up until 2020. By 2022/2023 there is a need for site densification for both macros and small cells, however the macros satisfy demand up to a point until and growth starts to flatten and the need for small cells continues to increase. The introduction of 700 MHz in 2026 and 2020 curtails the need to build more sites. However, the growth in small cells in suburban is greater than the urban and rural due to hot-spot nature of emerging demand. The upgrade in macros becomes almost exhausted and the rapid requirement for small cells begins to take over from around 2025. The introduction of 700 MHz clearly flattens the trend. A different pattern can be seen for the urban area where upgrades and spectrum satisfy demand up to 2022 after which an increase in macros are needed. It is not until 2023 that more small cells are required with almost a 13% increase over a 5 year period in the never case. This is reduced to 6% increase for 2020 case in small cells over a 5 year period and 8% increase for 2026 case in small cells over a 5 year period as can be seen in Figure 4-17. 107

250 600 Number of macro sites 230 210 190 170 150 130 110 Number of small cells 500 400 300 200 100 Rur Lincs, Never Rur Lincs, 2026 Rur Lincs, 2020 Sub Lon, Never Sub Lon, 2026 Sub Lon, 2020 Urb Lon, Never Urb Lon, 2026 Urb Lon, 2020 90 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-17 Summary of site count (Macros and small cells) across study areas and timing of 700 MHz Number of macro sites, relative to 2012 x1.25 x1.20 x1.15 x1.10 x1.05 Rur Lincs, Never Rur Lincs, 2026 Rur Lincs, 2020 Sub Lon, Never Sub Lon, 2026 Sub Lon, 2020 Urb Lon, Never Urb Lon, 2026 Urb Lon, 2020 Number of small cells, relative to 2012 x17 x15 x13 x11 x9 x7 x5 x3 x1.00 x1 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-18 Summary of number of sites (Macros and small cells) relative 2012 across study areas and timing of 700 MHz The plots in Figure 4-19 provide the cost savings summarised for each of the study areas and how the timing of 700 MHz (2020 and 2026) has an impact on the cost compared against the never case. Saving (relative to no 700 MHz) 60% 50% 40% 30% 20% 10% 21% 19% 42% 31% 28% 28% 21% 35% 52% 41% 55% 57% Network Cost saving (to 2040) New site saving (macro) New site saving (total) 22% 22% 21% 18% 15% 11% 0% 2026 2020 2026 2020 2026 2020 Urban Suburban Rural Figure 4-19 Relative savings in network costs (to 2040) and new cell sites (by 2030) arising from the availability of 700 MHz in 2020 or 2026 (mid demand and mid capacity scenarios) 108

We found that introducing 700MHz earlier in the timeframe does make a difference in the following way: In Urban London, network cost savings of 217% are possible if 700MHz is available from 2026 and 28% if it is available from 2020. In rural Lincolnshire, cost savings of 11% are possible if 700MHz is available from 2026 and 15% if it is available from 2020. In Suburban London, cost savings of 21% are possible if 700MHz is available from 2026 and 41% if it is available from 2020. These savings are driven by sub 1GHz spectrum (800 & 900MHz) becoming heavily utilised in locations of peak demand so deploying more low frequency, although 700MHz has the same propagation characteristics as the other sub 1GHz bands, the greater amount of bandwidth available allows capacity to be provided more cheaply. In the urban and suburban study areas the impact of 700MHz is more pronounced compared to rural Lincolnshire. This is because the capacity crunch occurs sooner in these areas and sites soon start to run out of spectrum. This means rapid densification of the network using both macros and small cells is required. Introducing 700 MHz early (2020) delays the capacity crunch and the need to spend pushed back several years. A more detailed look at the results reveals the impact from introducing 700 MHz early. The graph of average bandwidth used per macro site below shows us that by 2027 all the available bandwidth for 700 MHz is used if released in 2020. It can be seen that the capacity crunch arising in 2022 (see Figure 4-17) causes a significant rise in the use of 700 MHz (almost 100% increase) in two years. Both suburban and rural areas benefit from 700 MHz in similar ways, the differences with rural compared to urban and suburban is the requirement to also provide coverage and thus the relative cost savings are slightly lower. The percent cost saving in all areas is greater than the percent increase in overall spectrum that 700MHz represents (approximately 6%). This illustrates the magnitude of the benefits 700 MHz could bring as a proportion of all available spectrum. We combine this effect with benefits brought about by indoor propagation advantages of sub 1GHz spectrum. The impact can be magnified due to the benefits of both the overall quantity of spectrum available and the advantages the propagation characteristics that sub 1 GHz can offer. 700 Average bandwidth used per macro site (MHz) 600 500 400 300 200 100 0 0 0 0 0 0 0 0 7 11 19 28 38 39 39 40 40 40 40 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 3600 MHz -3800 MHz 3600 MHz -3800 MHz (UKB) 2700-3100 MHz 2600MHz 2300 MHz (2310-2390 MHz) 2100 MHz TDD (2010-2025 MHz) 2100 MHZ TDD (1900-1920 MHz) 1452-1492 MHz 3400 MHz - 3600 MHz 3400 MHz - 3600 MHz (UKB) 2600 MHz 2100 MHz 1900 MHz (1980-2010 MHz) 1800 MHz 900 MHz 800 MHz 700 MHz Figure 4-20 Average bandwidth used per macro site in urban London (Scenario 7) 2020 109

4.4 Results from high demand cases We analyse the impact of introducing 700MHz spectrum taking the high case scenario results 10-15 as the data for analysis. We focus specifically on scenarios 12 and 13 which are for the rural study area and the following figures provide details of the site evolution and also for the cost advantage in each case. Figure 4-21 shows the site evolution over the project time frame which consists of increase in the number of sites for both macros and small cells but also many site upgrades. A site configuration starts in 2012 as a 3 sector 2 transmit antenna macro which can be upgraded to a 3 sector 4 or 8 antenna macro in addition to a 6 sector 2 antenna macro. It can be seen from Figure 4-21 that 6 sector 2 antenna macros are the configuration upgrades mostly deployed across the whole timeframe. There is also an increase in the number of both macro sites and small cells which start to rapidly increase from 2017. There is a continuous requirement to upgrade sites and densify the network this is because the available spectrum quickly becomes fully utilised each year. However, we do see a positive impact of introducing 700 MHz in 2026 against the never case. We see that 700 MHz when introduced delays the need to upgrade and build new sites thus creating cost savings to the end of the time frame. In the rural case there are greater savings compared to urban and suburban, this is primarily due to the need to continually deliver coverage over the whole timeframe which also provides sufficient capacity. 1400 Outdoor small cell, 1-2 sectors, 2-4 antennas 1200 Macro, 6 sectors, 2 antennas 1000 Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas 274 339 Number of sites 800 600 400 200 0 222 165 126 133 783 96 682 71 585 48 428 520 33 472 19 363 16 292 0 1 13 43 74 102 132 157 183 205 247 7 7 7 7 7 8 12 157 156 144 116 96 74 55 53 58 66 63 85 74 109 69 74 105 148 101 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-21Total number of sites for high case rural study area (Scenario 12) 2026 110

1800 1600 1400 1200 Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas 462 Number of sites 1000 800 600 400 200 0 388 306 248 183 126 880 96 769 670 71 598 48 428 520 33 19 292 363 07 17 13 7 43 7 7 8 12 16 74 102 132 157 183 205 247 157 156 144 185 116 96 74 55 53 58 66 63 85 74 109 86 80 116 115 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-22 Total number of sites case rural study area (Scenario 13) no 700 MHz Number of macro sites 1400 1200 1000 800 600 400 200 0 Rur Lincs, Never Rur Lincs, 2026 Sub Lon, Never Sub Lon, 2026 Urb Lon, Never Urb Lon, 2026 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Number of small cells 6000 5000 4000 3000 2000 1000 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-23 Summary of site count across study areas and timing of 700 MHz We compare the trend in site evolution between the rural study area and urban study area to see the contrast in site type configurations deployed and upgrade evolution for the high demand never case. Figure 4-24 shows the site evolution for the urban study area. The data plotted for this scenario and scenario 10 (2026 case) only reaches the year 2027 and not 2030. This is because the new site placement algorithm in the model is unable to find a suitable position for a new macro or small cell. This is because all tried locations for a new macro are closer than 340m to other macros, and all tried locations for a new small cell are closer than 18m to other small cells. Once these limits have been reached no further deployments or upgrades can be made. Outdoor small cells are the predominant site type configuration in this case. This is because of the limited number of macros that can be deployed towards the end of the time frame thus depending on further upgrades to 6 sectors and exponential increase in the deployment of small cells to meet the demand growth. 111

6000 5000 4000 Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas Number of sites 3000 2000 1000 0 5425 4627 3970 3308 2934 2517 2162 2297 1769 881 1186 574 360 360 360 360 95 95 95 103 122 136 149 154 159 166 170 171 174 175 176 177 0 0 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-24 Total number of sites for high case urban study area (Scenario 11) never (Results shown up to year 2027) High demand, low capacity 25% Saving (relative to no 700 MHz) 20% 15% 10% 5% 0% -5% 13% 19% 15% 12% 5% 3% 2% Rural Suburban Urban -1% 6% Network cost saving New site saving (macro) New site saving (total) Figure 4-25 Cost of advantage across all study areas for high demand and all timings for 700 MHz There is a reduced cost saving from using 700 MHz in this high demand case as shown in Figure 4-25 than the equivalent mid case values. This is because as much available capacity would need to be utilised as soon as possible to meet demand. More specifically, in this scenario it means 100% of the bandwidth available in 700 MHz is used straightaway, as shown in Figure 4-26, in addition to using more sites. This is compared to the mid case for Urban London which used just over 60% of the available 700 MHz bandwidth in the first 3 years thus increased cost savings can be made. 112

120.0% 700 MHz 100.0% 2100 MHz 1800 MHz 800 MHz 900 MHz 1800 MHz 80.0% 1900 MHz (1980-2010 MHz) 2100 MHz 2600 MHz 60.0% 3400 MHz - 3600 MHz (UKB) 3400 MHz - 3600 MHz 1452-1492 MHz 40.0% 2100 MHZ TDD (1900-1920 MHz) 2100 MHz TDD (2010-2025 MHz) 2300 MHz (2310-2390 MHz) 20.0% 2600MHz 2700-3100 MHz 3600 MHz -3800 MHz (UKB) 0.0% 2012 2013 2014 2015 2016 2017 2018 2019 1452-1492 MHz 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 3600 MHz -3800 MHz 120.0% 700 MHz 100.0% 2100 MHz 1800 MHz 800 MHz 900 MHz 1800 MHz 80.0% 1900 MHz (1980-2010 MHz) 2100 MHz 60.0% 1452-1492 MHz 2600 MHz 3400 MHz - 3600 MHz (UKB) 3400 MHz - 3600 MHz 1452-1492 MHz 40.0% 2100 MHZ TDD (1900-1920 MHz) 2100 MHz TDD (2010-2025 MHz) 2300 MHz (2310-2390 MHz) 20.0% 2600MHz 2700-3100 MHz 3600 MHz -3800 MHz (UKB) 0.0% 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 3600 MHz -3800 MHz Figure 4-26 Utilisation of bandwidth urban London Scenario 11 (top) Scenario 3 (bottom) 2026 However, in terms of the actual costs of building a network this size would be deemed far too great to ever deploy in reality. This means an operator would need to use alternative less costly means to cap the demand. This would normally be treated by capping data and/or using strict price plans to keep demand to a reasonable level or traffic shaping and throttling back access of heavy users of the network. Furthermore, this high demand case is also interesting because it shows the direction of travel in that we would expect cost savings to increase as demand increases from our mid case. However, the cost saving is still moderate even when demand is very high and the network cost is infeasibly large. 113

4.5 Results from low demand cases The low demand scenario cases were modelled using high capacity elements including the more spectrum scenario, the high case spectrum efficiency and low offload case. The aim of this combination was to determine: The impact of having 700 MHz available in 2026 versus the never case for all study areas The impact of how all other spectrum bands and enhanced capacity techniques provides capacity The costs of providing capacity We first compare the impact of having 700 MHz in 2026 versus the never case for the Lincolnshire study area (Scenarios 18 and 19). Figure 4-27 shows that 3 sector 2 antenna macros are the main configuration upgrades deployed in this scenario along with only 2 6- sector 2-antenna macros. There is a gradual increase in the number of small cells which doubles over the 18 year timeframe and a 7% increase in the total number of macro sites. The low demand shows that there is very little spend on more capacity required, there is sufficient capacity from existing spectrum. There is little requirement for upgrades or new site builds on that basis. Some of the other low frequency spectrum is utilised but almost all demand is served from existing spectrum. 190 185 Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas 180 Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Number of sites 175 170 165 160 155 150 Macro, 3 sector, 2 antennas 8 8 8 7 7 8 8 8 0 0 0 1 2 01 01 2 1 1 157 157 157 156 156 156 155 156 13 10 10 9 9 9 9 10 2 2 2 1 2 2 2 2 2 1 1 1 1 1 1 1 14 13 2 2 1 1 158 158 158 158 158 159 160 161 162 163 15 2 1 165 145 140 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-27 Total number of sites for low case rural study area (Scenario 18) 2026 There is no difference in the number of sites or the choice of configuration when introducing 700 MHz in 2026. This is because there is sufficient capacity from both the available existing spectrum and spectral efficiency that even without the bandwidth available from 700 MHz there is no need to increase the number of sites. This aligns with our high level analysis which showed no new sites are required when there is lots of capacity to meet the very low demand growth. 114

190 185 Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas Number of sites 180 175 170 165 160 155 150 Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas 8 8 8 7 7 8 8 8 0 0 0 1 2 01 01 2 1 1 157 157 157 156 156 156 155 156 13 10 10 9 9 9 9 10 2 2 2 1 2 2 2 2 2 1 1 1 1 1 1 1 14 13 2 2 1 1 158 158 158 158 158 159 160 161 162 163 15 2 1 165 145 140 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-28 Total number of sites for low case rural study area (Scenario 19) no 700 MHz Figure 4-29 shows the very limited increase in the number of new macro sites across each of the study areas. There are only marginal increases of macros in both the urban and suburban study areas, which suggest that the cost effective solutions are to upgrade or deploy small cells to meet the low rate of demand increase. Number of macro sites 500 450 400 350 300 250 200 150 100 50 0 Rur Lincs, Never Rur Lincs, 2026 Sub Lon, Never Sub Lon, 2026 Urb Lon, Never Urb Lon, 2026 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Number of small cells 500 450 400 350 300 250 200 150 100 50 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-29 Summary of site count across study areas and timing of 700 MHz This means there is no cost differences between 700 MHz introduced in 2026 and never across all of the study areas. Rural Lincolnshire however, requires the highest total quantity of macro sites and fewest small cells compared across all the study areas this is due to the requirement for providing coverage. Comparing this to urban London for example, small cells are the majority configuration of site types deployed to meet this level of demand as shown in Figure 4-30. 115

700 600 500 Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas Number of sites 400 300 360 360 360 361 361 361 361 361 361 361 361 361 361 361 361 361 361 361 361 200 100 0 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-30 Total number of sites for low case urban study area (Scenario 16) 2026 We found that in the low demand case the importance of 700MHz is reduced as there is already sufficient bandwidth available across the whole timeframe. However, we acknowledge the bands other properties of providing very good in-building coverage targeting the hard to reach users deep indoors. 116

4.6 Role of 700 MHz for capacity The influence of demand on the importance of 700MHz is underlined when we look at utilisation as in Figure 4-31 below. It can be seen that the 700 MHz band serves the most demand compared to the other sub 1 GHz bands by 2030. This occurs because 700 MHz has the highest available bandwidth compared to 800 MHz and 900 MHz and thus provides more capacity. This means the deployment of 700 MHz spectrum can introduce relief into a capacity constrained network by soaking up more demand than the other sub 1 GHz bands but can also serve a much wider area compared to bands above 1 GHz. Demand (Mbps) 1000000 900000 800000 700000 600000 500000 400000 300000 Offload devices Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas 200000 100000 0 Figure 4-31 Demand served by frequency band in 2030 (Scenario 9 Mid case Sub London 2020) Demand (Mbps) 350000 300000 250000 200000 150000 Offload devices Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas 100000 50000 0 Figure 4-32 Demand served by frequency band in 2030 (Scenario 8 Mid case Rural Lincs 2020) 117

Another example of 700 MHz delivering increased benefits compared to the other sub 1 GHz bands in Rural Lincolnshire can be seen in Figure 4-32. The role of 700 MHz in rural areas is perhaps more compelling as using this band it is cost effective to serve both coverage and capacity. The observations that can be made from Figure 4-33 below show how 700 MHz performs in terms of capacity served. The plots show how by 2022 to 2024, 4 years after being released, the band begins to exceed the percentage of total spectrum offered by the band. This means the benefits in terms of supplied capacity outweighs the cost in terms of spectrum used and thus more bang per buck. 16% 14% % of total traffic served by 700 MHz 12% 10% 8% 6% 4% 2% 0% 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Sub: Mid 2020 Sub: Mid 2026 Urb: Mid 2020 Urb: Mid 2026 Rur: Mid 2020 Rur: Mid 2026 % of 700 MHz - Mid Figure 4-33 Proportion of traffic served by 700 MHz against percentage of total spectrum contribution from 700 MHz The chart in Figure 4-33 also shows that if 700 MHz is introduced in 2026 the benefits of timing are reduced. This is because more alternative spectrum bands become available thus limiting its ability to serve as much demand if released earlier. 4.7 Results from sensitivity analyses In the following two sections we discuss in detail the results from undertaking further sensitivity analyses in each of the study areas which are all based on the mid demand input. In Figure 4-34 below we present a summary results table of the other 18 scenarios that were modelled to understand further the impact and utility of 700 MHz under various offload and spectrum conditions. 118

Area Inputs High low offload 700MHz Macro sites Small cell sites Site savings 2030 Cumulative Cost, M Saving of 700MHz Offload Cost, M Spectrum Monthly from in 2012 in 2030 in 2012 in 2030 Macro Small Total to 2030 to 2040 to 2030 to 2040 to 2030 to 2040 cost, M cost/user, 22 Rural Lincs Mid demand low offload2020 157 189 7 48 24% -24% 3% 8.018 10.946 10.3% 11.6% 23.013 29.871 56.256752 0.050 31.031 40.818 23 Rural Lincs Mid demand low offloadnever 157 199 7 40 - - - 8.941 12.386 0.0% 0.0% 23.013 29.871 36.423 0.055 31.955 42.257 24 Urb Lon Mid demand low offload2020 95 108 360 453 32% 26% 26% 4.488 7.050 24.0% 24.6% 22.502 29.299 137.390 0.011 26.990 36.349 25 Urb Lon Mid demand low offloadnever 95 114 360 485 - - - 5.905 9.351 0.0% 0.0% 22.502 29.299 92.836 0.015 28.407 38.650 26 Sub Lon Mid demand low offload2020 227 237 10 118 60% 36% 39% 7.493 10.322 30.5% 33.8% 37.342 48.463 108.344 0.025 44.835 58.784 27 Sub Lon Mid demand low offloadnever 227 252 10 179 - - - 10.778 15.583 0.0% 0.0% 37.342 48.463 73.189 0.035 48.120 64.045 28 Rural Lincs Mid demand high offload2020 157 187 7 25 29% -6% 19% 7.234 9.691 12.2% 15.3% 30.344 41.107 55.748 0.045 37.578 50.798 29 Rural Lincs Mid demand high offloadnever 157 199 7 24 - - - 8.243 11.437 0.0% 0.0% 30.344 41.107 34.697 0.051 38.587 52.544 30 Urb Lon Mid demand high offload2020 95 100 360 423 38% 50% 49% 3.257 4.726 30.0% 35.0% 28.666 38.797 137.390 0.008 31.923 43.524 31 Urb Lon Mid demand high offloadnever 95 103 360 485 - - - 4.654 7.270 0.0% 0.0% 28.666 38.797 92.836 0.012 33.320 46.067 32 Sub Lon Mid demand high offload2020 227 230 10 45 67% 71% 71% 5.102 6.317 35.0% 41.7% 49.464 66.960 108.405 0.017 54.566 73.277 33 Sub Lon Mid demand high offloadnever 227 236 10 132 - - - 7.848 10.833 0.0% 0.0% 49.464 66.960 73.250 0.026 57.313 77.793 Spectrum sensitivity 34 Rural Lincs Mid dem_se spectrum more 2020 157 188 7 25 31% 18% 27% 7.158 9.676 19.5% 21.5% 25.330 33.385 57.606 0.045 32.488 43.061 35 Rural Lincs Mid dem_se spectrum less 2020 157 192 7 37 22% -36% 3% 7.853 10.826 11.7% 12.2% 25.330 33.385 49.685 0.049 33.183 44.212 36 Urb Lon Mid dem_se spectrum more 2020 95 98 360 400 81% 67% 69% 2.243 3.223 42.8% 48.2% 24.432 32.241 142.328 0.006 26.676 35.463 37 Urb Lon Mid dem_se spectrum less 2020 95 132 360 611-131% -107% -110% 14.496 21.686-168.3% -151.8% 24.432 32.241 118.925 0.037 38.929 53.926 38 Sub Lon Mid dem_se spectrum more 2020 227 231 10 59 80% 68% 69% 5.330 6.808 15.8% 18.8% 41.146 54.207 111.975 0.018 46.476 61.015 39 Sub Lon Mid dem_se spectrum less 2020 227 292 10 158-225% 3% -24% 14.986 22.475-136.6% -58.5% 41.146 54.207 93.754 0.049 56.132 76.682 Network & offload M to 2030 Total cost Network & offload M to 2040 Figure 4-34 Results summary table of offload and spectrum sensitivity analysis 119

4.8 Results from offload sensitivity The first 12 scenarios investigated the impact of high and low offload across each of the study areas for the 2020 and never cases. Offload is a useful metric to determine how 700 MHz can help serve the indoor demand locations across the study areas. The offload sensitivity shows how the rollout of capacity differs between the low, mid and high offload scenarios. The plots shown in Figure 4-35 below highlight the patterns of site builds for both macrocells and small cells in each of the study areas. The general trend that occurs across each of the study areas is the increased number of sites for the low offload case compared against the mid and high cases. We observe that for the low offload case increased number of macrocells and small cells are required to meet demand across each of the study areas. This means demand is exhausting both spectrum and technology earlier in the low offload case, compared to the mid and high cases, resulting in more site builds and thus higher costs. The urban and suburban areas demonstrate similar effects in relation to offload sensitivity. There is a requirement for new site builds in the mid and low offload cases around 2020 for suburban and 2023 for urban. In the high offload case there is a much reduced need for new macrocells with a 5% increase in macrocells in urban (2012 to 2030) and a 1% increase in macrocells for suburban across the timeframe. In the rural study area the effects of offload are not so clear cut compared to urban and suburban study areas. The impact of serving coverage and capacity in the rural area causes the number of macrocells to be broadly similar across the variation in offload. In some years the high offload case requires fewer macrocells but as the capacity crunch starts around 2025 the number of sites is similar within two or three sites difference. In contrast the number of small cells does vary across each of the study areas and across the scenarios. The number of small cells is sensitive to offload since it is smaller cells that are the most likely to serve the harder to reach indoor demand locations. Most notably there is an increase of 20% in small cells across the time frame for urban and an almost 12-fold increase in small cells for suburban in the low offload scenario. 120

250 230 210 Number of macro sites 190 170 150 130 110 Rur Lincs, HighOff,2020 Rur Lincs, LowOff,2020 Rur Lincs, MidOff,2020 Sub Lon, HighOff,2020 Sub Lon, LowOff,2020 Sub Lon, MidOff,2020 Urb Lon, HighOff,2020 Urb Lon, LowOff,2020 Urb Lon, MidOff,2020 90 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Macrocells 2022 2023 2024 2025 2026 2027 2028 2029 2030 455 405 Number of macro sites 355 305 255 205 155 105 55 Rur Lincs, HighOff,2020 Rur Lincs, LowOff,2020 Rur Lincs, MidOff,2020 Sub Lon, HighOff,2020 Sub Lon, LowOff,2020 Sub Lon, MidOff,2020 Urb Lon, HighOff,2020 Urb Lon, LowOff,2020 Urb Lon, MidOff,2020 5 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Small Cells Figure 4-35 Influence of 700 MHz availability on growth in cell sites for mid demand, low/high offload scenarios We investigate in more detail the effects on the site evolution and band utilisation for the suburban study are for varying offload scenarios. The graphs shown in Figure 4-36, Figure 4-37 and Figure 4-38, illustrate in more detail the site evolution between each of the offload scenarios. In the mid demand mid offload scenario (scenario 9) we see the dominance of the 6 sector 3 antenna site configuration with growth in the number of sites mainly coming from small cells in the latter 5 to 6 years of the timeframe. 121

The pattern, although the same for the low offload case, shows an increased number of small cells and a similar number of macrocells. Finally, in the high offload case we observe the much reduced requirement for small cells, with only 45 needed by 2030 compared to 118 by 2030 for the low offload case. 350 Outdoor small cell, 1-2 sectors, 2-4 antennas 300 Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas 250 Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas 10 10 10 11 11 12 12 13 13 13 13 13 17 21 23 30 41 57 75 Number of sites 200 150 208 211 212 213 214 215 217 217 218 220 221 221 222 223 223 225 226 227 230 100 50 0 0 0 19 0 0 16 15 14 10 12 20 10 8 21 31 8 7 31 53 1 43 1 43 1 3 2 2 2 1 2 01 4 30 4 20 4 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-36 Total number of sites for mid case mid offload suburban London area (Scenario 9) 2020 400 Outdoor small cell, 1-2 sectors, 2-4 antennas 350 Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas Number of sites 300 250 200 150 Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas 10 10 10 10 11 12 14 16 16 17 20 20 29 35 40 53 66 88 118 100 208 209 211 212 215 216 220 220 220 223 224 226 226 226 226 227 228 229 231 50 0 0 01 0 19 2 02 17 14 14 02 0 11 10 2 12 5 21 5 21 5 21 3 21 3 21 21 21 31 31 31 31 2 31 2 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-37 Total number of sites for mid demand low offload suburban London area (Scenario 26) 2020 122

350 Outdoor small cell, 1-2 sectors, 2-4 antennas 300 Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas 250 Macro, 3 sector, 2 antennas 10 10 10 10 10 11 11 14 14 14 14 14 15 15 16 19 33 39 45 Number of sites 200 150 208 211 212 212 213 216 218 221 221 222 223 223 223 223 223 223 223 223 223 100 50 0 0 0 19 10 10 16 20 14 14 12 1 9 1 7 14 23 1 21 21 21 21 21 21 21 12 12 41 2 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-38 Total number of sites for mid demand high offload suburban London area (Scenario 32) 2020 The final network costs to 2040 are presented in Figure 4-39 which shows how the costs vary across the low, mid and high offload scenarios and each of the study areas. The general trend of costs shows that in each case the low offload is the most expensive, with the mid offload case the next most expensive and the high offload case the least expensive. Since this study is focusing on the utility of 700 MHz we will analyse the cost savings against the 2020 case in more detail. Network costs to 2040 ( m) 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0-7.0 6.2 Lo Med 4.7 Hi 9.4 8.6 7.3 Lo Med Hi 10.3 Lo 8.4 Med 6.3 Hi 15.6 14.2 Lo Med 12.4 12.3 10.8 10.9 11.4 10.5 9.7 Hi Lo Med Hi Lo Med 2020 Never 2020 Never 2020 Never Urban Urban Suburban Suburban Rural Rural Hi Figure 4-39 Impact of varying offload assumptions on network costs (to 2040), with and without availability of 700 MHz in 2020 (mid demand and mid capacity scenarios). Costs should be treated as illustrative and relative rather than absolute. 123

Figure 4-40 shows the utilisation of the low, mid and high frequency groups (<1 GHz, 1-2.1 GHz and >2.1 GHz) across time between each of the offload scenarios. This plot illustrates the differences in the proportion of band utilisation and the ability to identify the timing of a spectrum crunch against each spectrum group. Utilisation of high/med/low bands 100% 90% 80% 70% 60% 50% 40% 30% Spectrum crunch Expensive building activity Low f low offload Med f low ofload High f low offload Low f mid offload Med f mid offload High f mid offload Low f high offload Med f high offload High f high offload 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-40 Band utilisation for low, mid and high frequencies groups across the suburban study area for low/mid/high offload scenarios It can be seen that the low frequency (low f) group has the highest band utilisation compared to the mid and high frequency groups. This is because usually the bandwidth is reduced compared the higher frequency groups and therefore used up quicker. The utility of 700 MHz can be determined from the low frequency group. However, introducing 700 MHz in 2020 across each of the offload scenarios has similar effects in delaying the spectrum crunch in around 2024. It can be seen that in the mid offload case there is around 5 year delay in spectrum crunch compared to a 4 year delay in the low offload case. This is extended to around 6 years in the high offload case. This is because sub 1 GHz spectrum would tend to serve the wide-area outdoor traffic first whilst capturing some of the indoor traffic. There is little difference in utilisation between the offload scenarios with only a year delay separating each case in the low frequency group. 4.9 Results from spectrum sensitivity The last 6 scenarios investigated the impact of high and low quantities of spectrum across each of the study areas for the 2020 cases. The spectrum sensitivity illustrates how a variation in the quantity and availability of spectrum can impact the utility of 700 MHz. The plots shown in Figure 4-41 below highlight the patterns of site builds for both macrocells and small cells in each of the study areas. It can be seen from the plots that a reduced quantity of spectrum can impact the number of additional sites required. The commencement of site densification also depends on when the spectrum bands begin to run out of capacity and site upgrade configurations. In the urban area we observe the need to start building macrocells as early as 2018 in the low spectrum scenario. This is compared to the mid case which does not start to build macrocells until 2024. This illustrates how the quantity and availability of spectrum is critical to meet demand. In the high case scenario the need to build macrocells does not start until 2029 thus delaying the need for new macrocells for almost the entire timeframe. 124

In the suburban study area there is no need to start building new macrocells until 2023 for the low spectrum case. This differs from urban since there is already a significant number of marcocells to serve the widespread demand. Site and spectrum upgrades would take place in the intervening period. In the mid and high case spectrum scenarios the number of additional macrocells is similar until around 2024. Beyond 2024 the number of additional macrocells increases in the mid case above that of the high case therefore reaching a capacity crunch earlier. In the rural study area it can be seen that the effects of spectrum sensitivity appear similar across the timeframe for each of the low, mid and high scenarios. This is due to the requirement of serving coverage and capacity in the rural area which causes the number of macrocells to be broadly similar (2-3 % variance) across the variation in spectrum. The number of small cells varies widely across each of the study areas and across the scenarios. The most notable impact on small cells takes place in both the urban and suburban study areas. An increase of 70% of small cells is required in the urban study area and a 15-fold increase in small cells for the suburban area. It can be seen that in the urban area the need for more small cells occurs in 2017 which means existing capacity techniques are becoming exhausted at this point in the low spectrum scenario. The introduction of 700 MHz in 2020 means the increase in small cells is stabilised until 2023 when a capacity crunch commences and more small cells are required. The pattern in the suburban area is slightly different although more small cells are required in 2018 under the low spectrum case. This is followed by steady growth until 2023 when the capacity crunch commences and a more rapid growth in small cells is observed from 2024 onwards. 125

Number of macro sites 340 290 240 190 Rur Lincs High spectrum 2020 Rur Lincs mid spectrum 2020 Rur Lincs low spectrum 2020 Sub Lon high spectrum 2020 Sub Lon mid spectrum 2020 Sub Lon low spectrum 2020 Urb Lon high spectrum 2020 Urb Lon mid spectrum 2020 Urb Lon low spectrum 2020 140 90 Number of macro sites 705 605 505 405 305 205 2012 2013 2014 2015 2016 2017 2018 2019 2020 Rur Lincs high spectrum 2020 Rur Lincs low spectrum 2020 Rur Lincs mid spectrum 2020 Sub Lon high spectrum 2020 Sub Lon low spectrum 2020 Sub Lon mid spectrum 2020 Urb Lon high spectrum 2020 Urb Lon low spectrum 2020 Urb Lon mid spectrum 2020 2021 Macrocells 2022 2023 2024 2025 2026 2027 2028 2029 2030 105 5 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Small Cells Figure 4-41 Influence of 700 MHz availability on growth in cell sites for mid demand, low/high offload scenarios We investigate in more detail the effects on the site evolution and band utilisation for the urban study are for varying spectrum scenarios. The graphs shown in Figure 4-42, Figure 4-43 and Figure 4-44, illustrate in more detail the site evolution between each of the spectrum scenarios. Using the mid spectrum case as the base line scenario (Figure 4-42), we observe that number of macrocells and small cells start to increase in 2024 and continue until the end 2022 2023 2024 2025 2026 2027 2028 2029 2030 126

of the period. This building activity means a spectrum crunch is taking place at that point. In contrast the first new small cell is built in 2016 in the low spectrum scenario with new small cells and macrocells increasing steadily until 2024 when both the number of small cells and macrocells increase rapidly. There is a requirement for additional small cells rather than macrocells in the urban study area. This is due to the hot spot nature of demand and the cost optimal way to satisfy that demand is by way of more small cells. 700 Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas 600 Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas 500 Macro, 3 sector, 2 antennas Number of sites 400 300 360 360 360 360 360 360 360 360 360 360 360 360 370 370 375 384 398 419 447 200 100 95 95 95 95 95 95 95 95 95 95 95 95 98 98 98 98 100 102 105 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-42 Total number of sites for mid case mid spectrum urban London area (Scenario 7) 2020 800 Outdoor small cell, 1-2 sectors, 2-4 antennas 700 Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas 600 Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas 500 Number of sites 400 300 360 360 360 360 361 361 374 396 396 403 408 422 471 518 538 562 579 599 611 200 100 0 95 95 95 95 95 96 97 103 104 106 107 110 116 122 123 124 126 129 132 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-43 Total number of sites for mid demand low spectrum suburban London area (Scenario 26) 2020 127

700 600 500 Outdoor small cell, 1-2 sectors, 2-4 antennas Macro, 6 sectors, 2 antennas Macro, 3 sector, 8 antennas Macro, 3 sector, 4 antennas Macro, 3 sector, 2 antennas Number of sites 400 300 360 360 360 360 360 360 360 360 360 360 360 360 360 360 364 372 381 387 400 200 100 0 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 95 96 97 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-44 Total number of sites for mid demand high spectrum urban London area (Scenario 32) 2020 The final network costs to 2040 can be seen in Figure 4-45 which shows how the costs vary across the low, mid and high spectrum scenarios and each of the study areas. The general trend of costs is similar to that for offload which shows that in each case the low spectrum is the most expensive, with the mid spectrum case the next most expensive and the high spectrum case the least expensive. Therefore, network costs are highly sensitive to the quantity and availability of spectrum but also the particular study area can impact on those costs. 800 Network costs to 2040 ( m) 700 600 500 400 300 200 100 0 611 447 400 132 106 98 late pub. sect. 158 292 Mid Hi late pub. sect. 75 59 37 25 25 236 231 192 192 188 Mid Hi late pub. sect. Small cells 2030 Macrocells 2030 Mid Urban Suburban Rural Hi Figure 4-45 Impact of varying the rate and quantity of public sector spectrum on cell sites (in 2030), with and without availability of (mid demand and mid capacity scenarios, 700 MHz in 2020). Costs should be treated as illustrative and relative rather than absolute. 128

Figure 4-46 shows the utilisation of the low, mid and high frequency groups (<1 GHz, 1-2.1 GHz and >2.1 GHz) across time between each of the spectrum scenarios. This plot illustrates the differences in the proportion of band utilisation and the ability to identify the timing of a spectrum crunch against each spectrum group. Utilisation of high/med/low bands 100% 90% 80% 70% 60% 50% 40% 30% Spectrum crunch Expensive building activity Low f Spec low Med f Spec low High f Spec low Low f Spec Mid Med f Spec mid High f Spec mid Low f Spec high Med f Spec high High f Spec high 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 4-46 Band utilisation for low, mid and high frequencies groups across the suburban study area for low/mid/high spectrum scenarios It can be seen that the low spectrum scenario quickly uses all frequency groups from 2012 onwards and the capacity crunch starts as early as 2016/2017. The utility of 700 MHz can be determined by the delay in the spectrum crunch by analysing the scale of increased available spectrum (low, mid and high case scenarios). In the low spectrum case there is no averting a spectrum crunch since there is insufficient capacity to introduce a delay. In the mid spectrum case a spectrum crunch is delayed by about 3 years and the high spectrum case a spectrum crunch is delayed by about 4 years. This demonstrates how 700 MHz can help relieve capacity on mobile broadband networks but also observe that if there are fewer spectrum bands available even 700 MHz may struggle to limit the onset of a spectrum crunch. 129

5. Overall findings 5.1 Introduction This chapter draws together the results and analysis from chapter 4 which are summarised into a set of overall summary of findings that satisfy the study objectives. We present the network cost savings that could be made from introducing 700 MHz either in 2020 or 2026 against each of the three main demand and supply scenarios. We highlight the benefits in terms of cost saving differences between the different regions for urban, suburban and rural areas. 5.2 The utilisation of 700 MHz delivers an overall cost saving We have considered the potential merits of an extensive range of potential capacityenhancing techniques in spectrum, technology and topology dimensions, summarised in Table 5-1. For each technique we have assigned, based on our research, a range of views as to the opportunity for it to increase capacity, as well as the cost of deploying the technique given an existing network, considering both capital and operational expenditure requirements over the whole study period. Our modelling uses this information to determine the combination of technologies which meets the demand on a cost efficient basis given our estimates of the costs of deploying each technology, accounting for factors such as the increasing cost of acquiring suitable sites as the density rises, the relative cost of upgrading existing sites versus building new ones, the costs of replacing and upgrading base station equipment over time, etc. 130

Table 5-1: Capacity-enhancing techniques: opportunities and challenges Spectrum / Technology / Topology Capacityenhancing technique Opportunities Challenges Spectrum Technology Public sector spectrum bands 700 MHz band White space UHF spectrum MIMO (multiple antenna technology) Enhanced modulation and coding efficiency Large quantities of high-frequency spectrum for capacity Useful physical properties for coverage and spectrum efficiency Wider bandwidth than currently available in sub 1GHz bands Increases supply of sub-1ghz spectrum Significant spectrum efficiency gains Potential to increase spectral efficiency from existing sites with little hardware change No identified spectrum below 1 GHz Relies on international harmonisation and associated standards support Relies on sufficient adoption to drive take-up by manufacturers in massmarket mobile devices Proliferation of bands increases device cost and may decrease performance International adoption in the European configuration for this band Uncertain availability and long timescale Alternative uses including broadcasting Proliferation of bands increases device cost and may decrease performance Constraints on protecting TV use limits opportunity to relatively short range devices Variability of supply by geographical location and over time Questionable harmonised support in mass market devices Impact limited at cell edge due to low signal quality Impact variable depending on spatial channel conditions Requires multiple antennas at base stations and mobile devices with impact on space, power consumption and practicality Large proportion of devices required to impact system capacity significantly Potential for further gains limited due to proximity of current technology to Shannon limit Gains typically require good signal strength and quality, so limited by interference when demand is high Coordinated Multipoint and Cloud RAN Joint processing of signals at different sites can transform interference into useful signals Permits centralised capacity to be shared Requires extensive, fast, low latency interconnect between sites (typically fibre) Centralising capacity may increase cost-effectiveness but does not directly impact maximum capacity density 131

Topology Carrier Aggregation Offload via femtocells Offload via Wi-Fi Extensive use of outdoor small cells Additional macrocells across dispersed geographical and temporal demand peaks Allows devices to access multiple increments of spectrum, potentially in multiple bands Facilitates refarming of existing spectrum Increases effective device bandwidth which can extend coverage Suitable for offloading indoor traffic which constitutes a large proportion of current and expected total demand Potentially closely targeted to locations with specific need Licenced spectrum to manage quality of service Improved coverage and user experience as well as capacity Supported by all mobile devices Suitable for offloading indoor traffic Widely deployed population of existing access points Growing support in mobile devices and for carrier-managed mobile experience Cost-effective supply of capacity to localised hotspots Extension of coverage to small settlements in rural areas Capacity delivered over wide area Does not directly increase available supply of capacity, just access to the available spectrum Support in devices may be limited to specific band combinations and RF performance may be less than a single band solution Interference and mobility coordination with wide network Availability of suitable backhaul To maintain or increase the proportion of offload, substantial increase over time in the capacity per femtocell will be required May be difficult to target on the most needy locations, reducing costeffectiveness Support for seamless call and encryption mobility Battery life concerns Users may disable capability Congestion of licence-exempt spectrum Availability of suitable backhaul To maintain proportion of offload, substantial increase over time in access point capacity will be required May be difficult to target on the most needy locations, reducing costeffectiveness Difficult to predict and locate the hotspots with precision and they may change location significantly over time Challenge in acquiring the right sites and providing power and backhaul Potential need for site sharing amongst operators to avoid excessive proliferation Lack of suitable sites Increased necessity for infrastructure sharing amongst operators 132

Impact of 700 MHz availability Following modelling of our mid-range demand and capacity (= spectrum, offload & spectrum efficiency) scenarios, Figure 5-1 illustrates how the number of macrocell sites rises for the suburban study area, while Figure 5-2 shows the impact on the number of small cell sites. In the absence of 700 MHz, a spectrum crunch is encountered between 2022 and 2025, where existing sites have been upgraded to the full extent of the available technology and spectrum, and the only option for meeting demand growth is to rapidly increase the number of both macrocell sites and small cells. The availability of 700 MHz in 2026 would minimise increases in sites beyond that point but too late to avoid the large site-build programme which is indicated. By contrast, bringing 700 MHz availability forward to 2020 reduces the scale of the rapid build-out programme delays it until towards the end of the study period. We also examine the impact of 700 MHz availability on incremental network costs. Network costs are presented throughout this report on the basis of present values in 2012 with social discount rates. Present values are calculated on the basis of incremental expenditure from 2012 to 2040, with the size of the network remaining constant beyond the study period (i.e. from 2030 to 2040). Given the uncertainties implicit in assigning costs to future network roll-out over the long study period, these costs should be treated as illustrative and as a basis for comparison between options, rather than as representing future costs on an absolute basis. Note also that this summary provides only the network costs, which do not include the costs of providing and operating indoor offload equipment. A similar impact is seen when examining the difference in network costs according to the availability of 700 MHz and indeed in the other study areas in Figure 5-3. The relative savings of the presence of 700 MHz in terms of both network costs and cell sites are summarised in Figure 5-4. Note that these savings are substantially greater than the 5%- 9% of relevant spectrum bands which 700 MHz spectrum represents, indicating how the particular physical properties of lower frequency spectrum can provide a benefit disproportionate to its quantity. Timing of 700 MHz availability relative to the spectrum crunch is critical: for example, network costs are reduced by 41% in the suburban area given 700 MHz in 2020, but by 21% with 700 MHz in 2026. We assumed a reasonable depth and consistency of indoor coverage consistent with other Ofcom studies. A greater depth and/or consistency could further increase the relative impact of low frequency spectrum such as 700 MHz. Similarly, we have assumed that the 700 MHz is available to support the whole market: if 700 MHz were made available to an operator who would not otherwise have such spectrum, the impact on that operator could be greater still. 133

Number of macro sites, relative to 2012 x1.10 x1.09 x1.08 x1.07 x1.06 x1.05 x1.04 x1.03 x1.02 x1.01 Sub Lon, Never Sub Lon, 2026 Sub Lon, 2020 x1.00 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Figure 5-1: Growth in macrocell sites for suburban area according to availability of 700 MHz (mid demand and capacity scenarios) 180 Number of small cells 160 140 120 100 80 60 40 Sub Lon, Never Sub Lon, 2026 Sub Lon, 2020 20 0 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Figure 5-2: Growth in outdoor small cell sites for suburban area according to availability of 700 MHz (mid demand and mid capacity scenarios) 2023 2024 2025 2026 2027 2028 2029 2030 134

Network costs to 2040 ( m) 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0 8.6 6.2 6.8 14.2 8.4 11.1 12.3 10.5 11.0 - Never 2020 2026 Never 2020 2026 Never 2020 2026 Urban Suburban Rural Figure 5-3: Impact of 700 MHz timing on network cost (mid demand and mid capacity scenarios). Costs should be treated as illustrative and relative rather than absolute. Saving (relative to no 700 MHz) 60% 50% 40% 30% 20% 10% 0% 21% 19% 42% 31% 28% 28% 21% 35% 52% 41% 55% 57% Network Cost saving (to 2040) New site saving (macro) New site saving (total) 22% 22% 21% 18% 15% 11% 2026 2020 2026 2020 2026 2020 Urban Suburban Rural Figure 5-4: Relative savings in network costs (to 2040) and new cell sites (by 2030) arising from the availability of 700 MHz in 2020 or 2026 (mid demand and mid capacity scenarios) Impact of offload assumptions on utility of 700 MHz One of the assumptions in our modelling is that a substantial fraction of demand which occurs in indoor locations can be offloaded via Wi-Fi and femtocells. We assume that offload in suburban and urban areas is currently around 40% of total traffic and will grow over the study period to 50% in our mid scenario (and a somewhat lower level in rural areas). Such an apparently modest growth in the fraction offloaded actually represents a very substantial growth in the volume of traffic, given the underlying total demand growth. It could be, therefore, that in practice the volume of offload is limited, or that practical factors such as backhaul capability and the need to target devices for the most needy locations limit the level of offload relative to our assumptions. Figure 5-5 shows that varying the potential level of offload (to 45 % by 2030 in our low scenario, and 60 % in our high scenario) varies the network costs, with a higher cost to meet the same demand to 135

compensate for lower offload. Figure 5-6 shows that lower offload also increases the number of cell sites needed. In all of our study environments, however, the network costs with the lowest level of offload in the presence of 700 MHz (in 2020) are still lower than those incurred with the highest level of offload in the absence of 700 MHz. Thus the presence of 700 MHz can reduce the necessary level of offload (and further reduce the associated costs of establishing and running the offload devices, which are not included in this comparison) or indeed can make a given level of offload more effective overall. Network costs to 2040 ( m) 18.0 16.0 14.0 12.0 10.0 8.0 6.0 4.0 2.0-7.0 6.2 Lo Med 4.7 Hi 9.4 8.6 7.3 Lo Med Hi 10.3 Lo 8.4 Med 6.3 Hi 15.6 14.2 Lo Med 12.4 12.3 10.8 10.9 11.4 10.5 9.7 Hi Lo Med Hi Lo Med 2020 Never 2020 Never 2020 Never Urban Urban Suburban Suburban Rural Rural Hi Figure 5-5: Impact of varying offload assumptions on network costs (to 2040), with and without availability of 700 MHz in 2020 (mid demand and mid capacity scenarios). Costs should be treated as illustrative and relative rather than absolute. 136

700 No. of cell sites 600 500 400 300 200 100 0 453447 423 485481485 118 75 45 179 162132 108106100114111103 Lo Med Hi Lo Med Hi 48 25 25 40 29 24 237236230 252247 236 189192187 199202199 Lo Med small cells in '30 macros in '30 Hi Lo Med Hi Lo Med Hi Lo Med Hi 2020 Never 2020 Never 2020 Never Urban Urban Suburban Suburban Rural Rural Figure 5-6: Impact of varying offload assumptions on cell sites (in 2030), with and without availability of 700 MHz in 2020 (mid demand and mid capacity scenarios) Impact of public sector spectrum availability A substantial portion of the spectrum growth represented in our mid-case spectrum scenario is from public sector spectrum holdings, representing some 22% of the total relevant spectrum by 2030. In Figure 5-8 we show the impact on the network costs of that spectrum becoming available more rapidly, reaching 24% of relevant spectrum ( hi ) or at a slower rate ( late pub. sect ), where it represents only 11% of spectrum in 2030. The corresponding impact on cell sites is given in Figure 5-7. It is clear that public sector spectrum forms a significant element in overall mobile capacity and its availability and usefulness (including the impact of harmonisation) can substantially impact on the scale of network build-out and the costs of meeting future demand, especially in urban and suburban areas. No. of cell sites 800 700 600 500 400 300 200 100 0 611 447 400 132 106 98 late pub. sect. 158 292 Mid Hi late pub. sect. 75 59 37 25 25 236 231 192 192 188 Mid Hi late pub. sect. Urban Suburban Rural Small cells 2030 Macrocells 2030 Mid Hi Figure 5-7: Impact of varying the rate and quantity of public sector spectrum on cell sites (in 2030), with and without availability of (mid demand and mid capacity scenarios, 700 MHz in 2020). 137

25 21.7 22.5 Network costs to 2040 ( m) 20 15 10 5 0 6.2 3.2 8.4 6.8 0 0 0 late pub. sect. Mid Hi late pub. sect. Mid Hi late pub. sect. 10.8 10.5 Mid Urban Suburban Rural 9.7 Hi Figure 5-8: Impact of varying the rate and quantity of public sector spectrum on network costs (to 2040), with and without availability of (mid demand and mid capacity scenarios, 700 MHz in 2020). Costs should be treated as illustrative and relative rather than absolute. Summary Given the long time period at issue here, there are very substantial uncertainties in the size and timing of both the demand for wireless services and the supply of capacity. This has been demonstrated by analysing the key sensitivities such as the timing of 700 MHz, the quantity and availability of spectrum and the level of offloaded demand. However, only the key assumptions could be modelled but there are various other assumptions that could materially impact the impact of 700 MHz, as summarised in Table 0-1 and in more detail in our report. Nevertheless, our study indicates the plausible ranges of these factors given current knowledge in the UK situation and provides a means of establishing the critical factors to balance demand and the supply of capacity with regard to both the scale and the cost of the necessary networks and establishes a guide to policy makers and operators as the period passes. Our key findings are summarised in Table 5-2. Overall, our study indicates clearly that both lower frequency and higher frequency spectrum have a role to play in future mobile capacity and that additional spectrum acts in combination with other sources of capacity such as small cells, offload and technology enhancements, with each approach benefiting from the presence of the others, rather than as substitutes. 138

Table 5-2: Summary of key findings Issue Finding based on our analysis Commentary Demand trends Impact of technological innovation Spectrum growth Impact of 700 MHz Based on current trends and our analysis of devices and user mobility, mobile broadband is projected to grow between 23x and 297x over the period 2012-30, with 80x being our mid case scenario. While growth will be high over the period, there is potential for the growth rate to reduce in the latter stages of this period. The non-uniformity of traffic between users, locations and environments (indoors and outdoors) and times of day is a major driver of the required form of capacity enhancement. The evolution of enhanced technologies, including via LTE- Advanced and its evolutions could deliver spectrum efficiency growth to existing cell sites of between 3.3x and 10.1x between 2012 and 2030, with a mid case of 6.2x. We have analysed the associated costs and provided guidance on the relative merits of the available techniques. Beyond the award of 800 MHz and 2.6 GHz, there is scope for substantial additional availability of harmonised spectrum for wireless services, representing around 350 MHz of additional spectrum for downlink capacity. This could deliver a growth in available spectrum capacity for the downlink between 7x and 13x over the period considered. This is expected to deliver sufficient capacity for networks of approximately the current scale of macrocells out to around 2024 with our mid-case growth and capacity assumptions (which include significant growth in macrocell spectrum efficiency and the number of small cells deployed). A 700 MHz band would represent only 5 to 9% of the relevant spectrum at 2030, but yields greater benefits due to its distinctive physical properties. These produce a benefit in terms of reducing the number of additional These ranges are not forecasts, but an indication of a plausible range of outcomes. Given this wide range, there is a need to secure options notably spectrum options for enhancing capacity, while making firm decisions on those options flexibly as the actual demand emerges. The inclusion of additional antennas in both base stations and mobile devices is key to achieving the higher growth rates, as is the successful adoption of advanced interference mitigation techniques supported by close coordination and lowlatency backhaul between base stations. Public sector spectrum release at frequencies above 2 GHz forms a major element of future spectrum capacity, and the rate at which it becomes available, harmonised, and included in mass-market data devices could vary the rate of overall spectrum availability significantly. Both the coverage and the spectrum efficiency properties of 700 MHz play a role in it delivering a greater benefit than the quantity available would suggest, including in its ability to deliver reliable indoor coverage from outdoor sites. The impact of 700 MHz varies substantially 139

Issue Finding based on our analysis Commentary Impact of outdoor small cells Impact of indoor traffic offload sites by between 18% and 52% (depending on the area) for 700 MHz availability in 2026 in the mid scenario for demand and capacity. Network costs are also reduced by between 11% and 27%. Earlier release in 2020 could substantially increase these benefits to 21%-57% site reduction and 15% to 41% network cost reduction. If operators can overcome challenges associated with determining localised areas of high demand and acquiring suitable sites to address them, then small cells are expected to play a significant role across all the scenarios studied. Growth varies substantially by region, but for our mid scenarios outdoor small cells represent 12% (rural) to 81% (urban) of all outdoor cells with 700 MHz availability in 2026, and somewhat higher without it. Indoor offload devices, whether using Wi-Fi or femtocells approaches in licence-exempt or licenced spectrum, already offload substantial traffic (around 30-40%) from wireless networks and this use is expected to increase, perhaps to as high as 60% by 2030. However, the costs can be substantial compared with outdoor network costs when widely deployed and this could limit offload deployments to some extent. If so, network costs are increased to compensate. The availability of 700 MHz in 2020 was found to mitigate this risk, reducing network costs in our lowest offload scenario to below those of our high offload scenario in the absence of 700 MHz. with geographical area, depending on the balance of coverage and capacity. Where coverage limitations dominate areas, there is a reduction in the rate at which new sites need to be built. Where capacity limitations dominate, 700 MHz delays the advent of the need to build additional sites, which can significantly affect the cost although the relative timing of the spectrum availability and the capacity crunch is critical. Outdoor small cells act to reduce the number of additional macrocell sites (and associated costs) which would otherwise be required in two ways: 1) They act as a low cost means of providing coverage to locations where the number of individuals affected is relatively small, for example in rural areas. This also helps the macrocells to continue to deliver wide area coverage without becoming range limited due to capacity constraints. 2) They deliver capacity to localised hotspots of demand, allowing the growing capacity of macrocells to meet the wide-area capacity needs. This applies to any area with a wide spatial variation of traffic needs, and we observe significant growth for this purpose across all our study areas. There are open questions concerning the enabling factors for offload quantities to keep up with the growth of demand, including availability of suitable backhaul, sufficiency of spectrum (whether licenced or licence-exempt) and the ability of offload devices to be targeted on the most effective locations. We recommend further study of these issues. However the uncertainties may be less when addressing some proportion of indoor demand from outdoor sites, in which case spectrum bands such as 700 MHz could yield an increased benefit. 140

5.3 Further work and other analyses This study has investigated the main cost differences of utilising 700 MHz against the three main demand scenarios and for several assumptions regarding the growth in network capacity. There are many possible combinations of inputs that could have been analysed to determine more specific differences of how 700 MHz could provide benefits or not in the future. The following sections describe how a difference in some of the key input assumptions could lead to an alternative outcome of using 700 MHz. 5.3.1 Impact of the differences between demand assumptions The demand assumptions in the study are what drives the size and shape of the capacity network built by the model. We modelled all critical demand cases in the study to determine a variety of sensitivity cases and the extremes. However, some other corner points could be explored by maintaining the mid capacity cases and varying demand. This will highlight the impact of timing (amongst other things) by introducing 700 MHz at earlier points in the timeframe. 5.3.2 Alternative offload assumptions In the study we assumed that offload provides an alternative means of transferring mobile network traffic to the fixed network. A shift in the assumptions based on consumers willingness to pay for devices or poor quality of service owing to unlicensed and crowded spectrum, could lead to higher costs to the mobile network. No explicit spectrum allowance is made for offload. It is assumed that offload devices would either operate in licence-exempt spectrum (as in the case of Wi-Fi) or in licenced spectrum in a way which does not significantly increase the overall spectrum requirement, either by successfully coordinating with macrocells in the same channels or else in dedicated channels either operator-specific or shared across the market with a high level of frequency reuse. Given these open questions, this represents an area where further study should be conducted. Nevertheless, we have accounted for levels of offload which are consistent with current trends and note that even if offload levels were half those which we have assumed, this would be well within the range of the demand scenarios we have examined. 5.3.3 Uncertainties in spectrum availability In the study we assumed there would be availability of spectrum across 17 different frequency bands. These bands were identified on the basis that they were suitable for mobile use and were (or could be) standardised and harmonised. However, it was recognised there are some uncertainties surrounding some of the bands identified. In particular, there is uncertainty regarding quantity and timing of the availability of the public sector and current non-mobile allocated bands which represented 40% of total available spectrum for the study. The assumptions for these spectrum bands were based on the latest public information available. However, by adjusting the quantity and timing of the availability of these bands could impact the results particularly in high demand cases when the spectrum bands become fully utilised over a short period of time. 141

5.3.4 Assumptions on a single network In order to simplify the modelling we assumed a single operator would deliver mobile broadband services over two shared networks with traffic equally split between them. However, this assumption may impact the costs to a single mobile operator since mobile operators will base the value of 700 MHz spectrum their own spectrum and site portfolios. Additionally, the assumption for the evolution towards site sharing can also impact the costs because it assumes no new individual operator sites will be built and in practice that may not be the case. 5.3.5 Practicality and challenges for deploying small cells We assumed that small cells could be deployed anywhere within the study area without consideration for the practicalities and limitations in doing so. Small cells still require planning permission and coordination and a proportion of the small cells deployed in the study area might not be deployed in practice or might not be as well-located as we have assumed. A useful analysis would be to understand the impact of suboptimal placement of small cells. 5.3.6 Assumptions on uniform distribution of demand We assumed that demand was not uniformly distributed across the study areas so as to represent a more practical and realistic environment. It could be argued that if demand were more uniformly distributed, which as discussed in Annex A5 is moving in that direction, the utility of 700 MHz would be increased due to the more consistent and spatial spread of demand. 5.3.7 Assumption on indoor/outdoor demand split The split between amount of indoor and outdoor demand was informed by current analyst data which illustrated the majority of demand consumption indoor with that trend set to continue in the future. A sensitivity analysis of a different indoor/outdoor demand split would potentially highlight the effects between lower frequency spectrum and higher frequency spectrum and difference in the ability to serve the indoor demand. 142

References i Spectrum in an age of innovation Ed Richards, Chief Executive, Ofcom, speech for ECTA Regulatory Conference, 29 th November 2011, http://media.ofcom.org.uk/2011/11/29/spectrumpolicy-in-the-dynamicage/?utm_source=updates&utm_medium=email&utm_campaign=spectrum-speech ii Mobile broadband with HSPA and LTE capacity and cost aspects, Nokia-Siemens Networks, May 2010 iii 2020: Beyond 4G. Radio evolution for the gigabit experience, Nokia-Siemens Networks, 2011 www.nokiasiemensnetworks.com/file/15036/beyond-4g?download iv Modelling the cost of heterogeneous wireless access networks, Klas Johansson and Jens Zander, Royal Institute of Technology Sweden, Anders Furuskär, Ericsson Research, 2007 v Mobile broadband busting the myth of the scissor effect, Mobile Broadband Strategy, 2010 vi Estimation of the potential deployment of small cell base stations in 2015, PicoChip, July 2011 vii Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2010 2015, Cisco, Feb 2011 viii 4G Capacity Gains report, Real Wireless, Jan 2011, http://stakeholders.ofcom.org.uk/binaries/research/technologyresearch/2011/4g/4gcapacitygainsfinalreport.pdf ix 3G coverage maps, Ofcom September 2009 x Mobile Infrastructure Project, Industry Stakeholder engagement, DCMS, January 2012 xi Creating a new mobile champion, Everything Everywhere, Sept 2010 http://www.download- telekom.de/dt/staticpage/92/75/30/100928- investor-event-everything-everywhere_927530.pdf xii xii Traffic and Market data report ON THE PULSE OF THE NETWORKED SOCIETY, Ericsson, November 2011, http://hugin.info/1061/r/1561267/483187.pdf xiii Worldwide mobile broadband connections to hit 445 million by 2015, Analysys Mason, July 2010 xiv Technology forecasting for telecommunications, Telektronikk, 2004 xv Capacity crunch in Asia, HSBC Research, June 2010, http://www.research.hsbc.com/midas/res/rdv?p=pdf&key=imjkf7r5xl&n=270222.pdf xvi Predicting Areas of Spectrum Shortage, PA Consulting, April 2009, http://stakeholders.ofcom.org.uk/binaries/research/technology-research/shortage.pdf xvii Predicting Areas of Spectrum Shortage, PA Consulting, April 2009, http://stakeholders.ofcom.org.uk/binaries/research/technology-research/ shortage.pdf on Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); Base Station (BS) radio transmission and reception (Release 10), 3GPP TS 36.104 V10.1.0 (2011-01) xix The timing of the consumer and operator features available from HSPA and LTE, Real Wireless, January 2012 xx HMT, Supplementary Guidance on The Green Book Appraisal and Evaluation in Central Government, 2011, http://www.hm-treasury.gov.uk/data_greenbook_supguidance.htm 143

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