An Infrastructure Cost Evaluation of Single- and Multi-Access Networks with Heterogeneous Traffic Density

Transcription

1 An Infastuctue Cost Evaluation of Single- and Multi-Access Netwoks with Heteogeneous Taffic Density Andes Fuuskä and Magnus Almgen Wieless Access Netwoks Eicsson Reseach Kista, Sweden [andes.fuuska, Abstact Taditional pefomance measues like capacity, cell adius and suppoted QoS ae often insufficient when compaing wieless netwoks with diffeent netwok achitectues and cost stuctues. Instead, in this pape, infastuctue cost is used to compae diffeent opeato deployed single- and multi-access wieless netwoks, including 3G, WLAN and poposed 4G adio access technologies. Fo this pupose a model fo the geogaphical distibution of taffic is intoduced. Despite the spatially nonunifom taffic demand, single-access solutions like WCDMA High-Speed Downlink Packet Access (HSDPA) o Long-Tem 3G Evolved, with high capacity maco cellula base stations, typically yield the lowest costs pe use. In paticula this holds fo a hypothetical Long-Tem 3G Evolved system opeating in 450MHz spectum, which indicates the impotance of good coveage. Opeato deployed WLAN-only solutions ae moe expensive even fo small factions of suppoted uses. Multi-access solutions, combining fo example WCDMA DCH o HSDPA with WLAN, do not seem to povide bette cost efficiency than standad hieachical cell stuctues in single-access systems. Instead, multi-access solutions have to be motivated by othe factos like peak data ates and spectum availability. Keywods: Infastuctue cost, Tele-economics, multi-access, WCDMA, 3G, Long-Tem 3G Evolution, 4G, WLAN I. INTRODUCTION Mobile netwok opeatos ae typically inteested in maximizing the pofit detemined by the evenue geneated by thei systems and thei costs. Taditional pefomance measues used fo single-access cellula systems, such as coveage and capacity, ae effective measues of the elative impovements fo specific systems. Consideing also deployment aspects and that diffeent systems typically have diffeent cost stuctue, technical measues, like spectal efficiency, ae howeve, as discussed in e.g. [1], insufficient to compae diffeent systems. Ideally both costs and evenues should be included in the analysis, as in [2], and availability of spectum, pevious assets, and othe stategic issues need to be taken into account. Due to difficulties in, e.g., pedicting end uses willingness to pay, this is quite complex. A simple initial step, fo elative compaisons only, is to compae the system cost fo equal potential evenues (to simplify; numbe of suppoted uses) and this is also the focus of this pape. Klas Johansson Wieless@KTH, The Royal Institute of Technology Electum 418, S Kista, Sweden klasj@adio.kth.se Moe specifically, the adio access netwok infastuctue cost is nomalized pe use and compaed between diffeent single- and multi-access system concepts as a function of taffic intensity pe use and elative use coveage. The system concepts compaed include the cellula systems WCDMA DCH, WCDMA HSDPA, and peliminay Long-Tem 3G Evolution and 4G poposals, as well as the WLAN system concepts IEEE b, a and g. Also multi-access combinations of these, an expected chaacteistic of futue wieless netwoks [3], ae included. To evaluate the benefits of the multi-access netwoks, a heteogeneous taffic density model is applied. Recently a numbe of wieless netwok infastuctue cost analyses fo single-access netwoks have been pesented, e.g. [1] and [2]. These conclude that the infastuctue cost, including both capital expenditues (CAPEX) and opeational expenditues (OPEX), is lagely popotional to the numbe of access points deployed. Equivalent cost figues pe access point, ae also pesented, which can be used to simply assess the total infastuctue cost fo a given deployment. Models of the spatial distibution of mobile uses have been pesented in e.g. [4] and [5]. This pape combines the above esults and extends the scope to cove multi-access netwoks. In what follows, Section II biefly discusses the impact of the spatial taffic distibution on the cost efficiency of diffeent single- and multi-access system concepts, and pesents the deployment pinciples used in this study. An oveview of the adio netwok, use behavio, and economical models and assumptions is given in Section III. Numeical esults ae pesented in Section IV, followed by conclusions in Section V. II. DEPLOYMENT ASPECTS In scenaios with homogeneous, unifom taffic densities, single-access solutions with only one type of access point manage to maximize cost efficiency. Fo example, with a high aea taffic demand mico cellula base stations may be most cost efficient, wheeas maco base stations typically yield the lowest cost in aeas with less taffic pe aea unit. Solutions with a mix of maco, mico and pico cells, as well as multi-access concepts, may be expected to be moe cost efficient than single access netwoks only in scenaios with heteogeneous taffic densities. Yet, this is not a sufficient condition. It is also equied that taffic peaks (hotspots) ae vey few and stong.

2 Taffic Density 1) Vaying but low (aveage) taffic density 2) Vaying and high Aveage Maco cell aea capacity Taffic Density Taffic Density 3) Stongly vaying, high, and coelated Mico cell aea capacity Figue 1. Simple example of taffic density vaiations ove space, and deployment of maco (light gey) and mico (dak gey) access points. This is explained by the following example based on maco and mico cellula base stations. Assume that a single-caie maco cell laye is deployed fo fundamental coveage. As depicted in the fist example in Figue 1, the capacity of this netwok is sufficient to seve taffic density pattens fo which the aveage is within the maco cell aea capacity. Local aeas with taffic demands exceeding the aea capacity ae suppoted. Then, if the aveage taffic density exceeds the total aea capacity of the fist maco caie, eithe a second maco caie, additional maco base stations o mico cells can be deployed. What solution that bings the lowest cost depends on the statistical distibution of taffic. In the second example, taffic is high and stongly vaying with many elatively small peaks. Then adding a caie to the maco-cellula laye, o deploying maco base stations moe densely, is typically most efficient. Deploying a mico cell in each of the many local taffic density peaks would equie a lage amount of mico sites, and hence be costly, since each mico base station would have excess capacity and be pooly utilized. In situations like the one in example thee, howeve, mico cells ae motivated. Hee, the peaks in taffic density ae vey stong and athe few, so that only a few mico cells need to be deployed, and the cost fo this is lowe than that of extending the maco laye. A heteogeneous taffic density alone is thus not sufficient fo motivating mico and pico cell, o multi-access solutions fom an infastuctue cost pespective. Thee ae also equiements on (i) a high oveall taffic density, (ii) stong vaiations in taffic density, and (iii) special spatial coelation popeties. A. Deployment Pinciple The deployment pinciple used in this study is to fist deploy maco cells fo full aea coveage, and then complement with mico o pico cells, o WLAN access points, whee it is needed fo capacity easons. In moe detail, fist, the system aea A sys is divided into N diffeent 40x40m elements. The (cente) position and the taffic geneated in element n ae denoted P n and TE n espectively. Fo each RAT, candidate access point sites ae positioned on a egula hexagonal gid, with site-to-site distances accoding to the AP cell adii. The position of AP m is denoted S m. Based on the site positions, an association between sites and taffic elements is made, so that the elements in the set S m belong to AP m. The association is done so that taffic elements ae associated with the closest site: S { n min{ d( AP, P } m} m = k k n ) = ag (1) whee d(ap k, P n ) is the distance between AP k and element n. The offeed taffic pe AP is calculated as: m T = TE (2) n In each site m, N m cells (tansceives) ae then deployed to fulfill the offeed taffic, while not exceeding the maximum numbe of cells pe AP, denoted N APmax : T N = m m min, N APmax m C, (3) whee C is the capacity pe access point of RAT. Note that if T m = 0, no access point is deployed. If T m > C, all the offeed taffic cannot be handled by RAT. In that case elements ae allocated in an inceasing ode of offeed taffic TE n until the maximum capacity pe AP C N APmax is eached. Remaining taffic that has to be seved with othe RATs (with a smalle cell adius and highe aea capacity) will then belong to elements with the highest taffic TE n. Moe fomally, the taffic elements S m ae soted in ode of offeed taffic and indexed n. The numbe of elements M max,m that ae seved by AP m is then detemined by: M M max,m = max M : TEn' C N APmax,m (4) n' = 1 Then, the offeed taffic in elements n =1.. M max m is set to zeo to detemine the offeed taffic fo the next RAT to be deployed, i.e., TE n' S m n 0 n' M = (5) TEn' n' > M max m max m Once the above deployment is completed, which esults in 100% coveage if no taffic emains afte the last RAT is deployed, the cost fo coveing smalle factions of uses is calculated. This is done though soting the access points in ode of suppoted taffic divided by the access point cost. Given the final deployment fo full coveage, deployment in this ode epesents the most cost efficient way to suppot a given taffic. It should be noted that no attempts have been made to optimize the deployment pinciple. Instead, the taget has been a simple pinciple that is easonably good and fai between system concepts. It could e.g. be noted that limiting WLAN access point positions to a egula gid is pobably not optimum, but neithe is allowing only one cell adius fo cellula maco, mico, and pico cells. This tadeoff is discussed futhe in [7].

3 Figue 2. A sample of a taffic density map and WCDMA maco and WLAN access point deployment. III. MODELS AND ASSUMPTIONS This section descibes the use behavio, system, and adio netwok models used to evaluate the diffeent system concepts. Macoscopic models ae used to enable a conceptual compaison between the concepts fo diffeent taffic densities. A. Taffic Density Models In ode to captue the effects discussed in Section II, a heteogeneous use behavio is assumed. In shot, based on the measuements and model poposed in [4] and statistics fom [6], it is assumed that the use density is log-nomally distibuted aound a lage-scale mean. The small scale standad deviation of this distibution is adjusted so that assumed peak values in use density ae achieved with easonable pobability. To fit the cell-level use density standad deviation to the value 0.4 (log-scale) epoted in [4], a spatial coelation is assumed between elements. Refeence use densities ae ceated by multiplying typical sububan (su) and city cente (cc) population densities, 500 and inhabitants/km 2 espectively, with an assumed sevice penetation of 90% and an opeato maket shae of 30%. Uses ae futhe chaacteized by an aveage busy hou taffic intensity, measued in data geneation pe unit time. As a basis fo this, the taffic intensity of a pivate voice use duing busy hou is used. This is assumed to be 20mElang x 10kbps = 0.2kbps. Multiplying this with a facto N then foms taffic intensity efeence values. As a efeence, assuming that 0.6% of the monthly taffic is geneated duing each busy hou (typical fo voice), a 1GB/month use coesponds to 13kbps, o N = 66. Taffic density maps (10x10km) ae ceated by multiplying the use densities and pe-use taffic intensities. The gay scale contou in Figue 2 depicts a ealization of taffic density geneated by the model. Note that no explicit sevice is assumed. The evaluation is applicable to all sevices fo which the system models, i.e. access point capacity and coveage, ae valid, and that ae within the capabilities of the access technology. These capabilities diffe significantly between some of the access technologies. Fo example, 4G concepts should be compaed with WCDMA only fo sevices suppoted by both netwoks. TABLE I. ACCESS POINT CHARACTERISTICS. Radius Capacity Cost Coeff. WCDMA DCH maco 1000m [3-9] x 1Mbps 1 (55/45%) WCDMA DCH mico 250m [1-2] x 1Mbps 0.45 (45/55%) WCDMA DCH pico 100m 1Mbps 0.3 (35/65%) WCDMA HS maco 1000m [3-9] x 2.5Mbps 1 (55/45%) WCDMA HS mico 250m [1-2] x 2.5Mbps 0.45 (45/55%) WCDMA HS pico 100m 2.5Mbps 0.3 (35/65%) S3G maco 1000m 3 x 15Mbps 1 (55/45%) S3G mico 250m 15Mbps 0.45 (45/55%) S3G pico 100m 15Mbps 0.3 (35/65%) S3G maco m 3 x 15Mbps 1 (55/45%) 4G 700m 3 x 100Mbps 1 (55/45%) 4G mico 175m 100Mbps 0.45 (45/55%) 4G pico 70m 1Gbps 0.3 (35/65%) 4G elay 1850m 100Mbps 6.4 (65/35%) IEEE b 40m 6Mbps 0.13 (3/97%) IEEE g 40m 22Mbps 0.13 (3/97%) IEEE a 20m 22Mbps 0.13 (3/97%) IEEE n 20m 100Mbps 0.13 (3/97%) B. System and Radio Netwok Models Access points of diffeent access technologies ae chaacteized with diffeent maximum cell adii and capacities; see Table I (heein a cell is defined as a combination of a secto and caie fequency). All figues ae fo the downlink and oughly valid fo an uban envionment without stict equiements fo indoo coveage. Howeve, with the simplified modeling used, without explicit adio netwok models, the models ae applicable fo abitay envionment, deployment and sevice scenaios fo which the system models ae valid. The WCDMA DCH and HS-DSCH figues, assuming a 15MHz spectum allocation, ae taken as efeence values, and Long-Tem 3G Evolved [8] (hencefoth shotly denoted S3G ) and 4G figues ae deived fom these. Fo S3G, a 20MHz spectum allocation is assumed. Togethe with a spectum efficiency assumption of 0.75bps/Hz/cell, this esults in a capacity pe cell of 15Mbps. The same powe density as fo WCDMA is also assumed, esulting in the same cell adius. To investigate the impact of coveage, a hypothetical S3G system opeating in 450MHz spectum, is also studied. Its cell adius is simply based on fequency diffeence and a path-loss exponent of 3.5. Fo 4G, a 100MHz spectum is assumed, togethe with a slightly impoved spectum efficiency of 1bps/Hz/cell. This esults in a capacity pe cell of 100Mbps. A fou times lowe powe density is assumed fo the wide 4G caie than fo WCDMA. Assuming a distance attenuation exponent of 3.5, this esults in a 30% educed cell adius. Mico and pico cell capacities ae assumed equal to the maco-cell capacities (pe cell). The WLAN figues assume single-cell, non-intefeed access points. In coodinated multi-cell scenaios these figues decease some 20-40% fo b and g. In noncoodinated multi-opeato scenaios, the capacity is shaed equally between the opeatos. A simple 2-hop egeneative elaying concept is also evaluated. It is assumed that the access point is suounded by a ing of six elay nodes, each with the same cell adius as a egula maco cell access point. This esults in an equivalent cell adius of 7 of the oiginal cell adius. The capacity is limited by the access point, and assumed to emain at 100Mbps despite the potentially favoable channel conditions towads the elay

4 Infastuctue Cost pe Month and Gbyte [ ] /month su1 Faction of Suppoted Uses 90% su10 cc1 su Taffic Density [Mbps/km2] Figue 3. Infastuctue cost pe 1GB/month use vesus taffic density fo 90% suppoted uses. nodes. Note that moe sophisticated elaying concepts than that evaluated hee exist, with potential to futhe impove coveage and capacity. The access points ae also chaacteized with the cost coefficients given in Table I. These estimate the total infastuctue cost associated with one access point, including CAPEX fo adio access netwok equipment and site build out, as well as OPEX fo site ental, tansmission, powe consumption and O&M ove a 10-yea peiod, assuming a 10% discount ate. The figues build on those used in [1], whee in tun equipment cost estimates wee povided by the Gatne Goup and othe cost estimates wee based on [2]. In this study mino updates fo adio netwok contolles, powe consumption and O&M, and addition of WLAN, also based on [2], have been made. The coefficients in Table I ae nomalized to an estimated value fo a cellula maco base station, assumed to be 300k (slightly highe than in [1] due to the above modifications). The components of the cost coefficients ae futhe discussed in [1] and [2], Table I meely includes the factional CAPEX and OPEX, which in tun ae dominated by site and tansmission costs espectively. The total infastuctue cost fo geen-field opeatos can be calculated as the numbe of access points of each type multiplied with the coesponding cost coefficients. Note that this model excludes costs fo coe netwok nodes as well as costs fo spectum (due to diffeences in egulation, a geneally applicable spectum cost model is vey difficult to define). This makes the costs incemental, i.e. measuing the additional cost fo coveing a new aea, once the coe netwok and spectum is paid fo. Teminal costs, as well administative costs, e.g. fo maketing and billing, ae also excluded. IV. NUMERICAL RESULTS In this chapte numeical esults ae pesented on the fom infastuctue cost pe tansfeed data unit (1GB) and month vesus taffic density and factional coveage. In Figue 3 90% of the taffic (uses) ae suppoted and in Figue 4 only a small faction, 20%, of the uses ae seved. Some efeence levels ae maked on the taffic density axis. These ae combinations of sububan (su) o city cente (cc) envionments as defined above, and taffic intensities pe use measued in N times voice (0.2kbps). On the cost axis, a efeence level of 30 pe cc10 su g WCDMA DCH WCDMA HS DCH & 11g HS & 11g S3G S3G 450 4G 4G elay cc100 cc1000 Infastuctue Cost pe Month and Gbyte [ ] /month su1 Faction of Suppoted Uses 20% su10 cc1 su Taffic Density [Mbps/km2] Figue 4. Infastuctue cost pe 1GB/month use vesus taffic density fo 20% suppoted uses. GB and month is maked. This is a ough estimate of what a typical use is willing to spend on mobile communications today. Geneally, fo all system concepts, the infastuctue cost pe GB deceases with taffic density while the systems ae coveage limited, and flattens when the system becomes capacity limited. A. Commecially Available Systems Beginning with the g WLAN and 90% of the taffic seved, it is seen that fo low taffic densities the cost pe GB is vey high. In a sububan envionment with a voice-like taffic intensity pe use (su1), the infastuctue cost eaches /GB/month. To get down to a easonable cost pe GB ( 30), a taffic density of 10 Mbps/km 2 is equied, appoximately coesponding to su500 o cc10 scenaios. Fo a faction of suppoted uses of only 20%, as shown in Figue 4, the cost pe use fo g deceases significantly (as expected). The easonable cost of 30/GB/month is now eached at 1Mbps/km 2 instead, o oughly a cc1 scenaio. This indicates the degee of coveage that can be expected to be pofitable fo WLAN only opeatos. WCDMA DCH and HSDPA yield about 50 times lowe cost fo modeate taffic densities. These systems each 30 pe GB and month aleady at 0.2Mbps/km 2 coesponding to su10 scenaios. WCDMA HSDPA becomes capacity limited at highe taffic densities than WCDMA DCH, and theefoe yields lowe costs at high taffic densities. The cossove point between WCDMA HSDPA and g is about 100Mbps/km 2, o cc100. With 20% of the uses coveed WCDMA HSDPA is moe expensive than WLAN at 30Mbps/km 2 (su1000/cc30), wheeas with 90% coveage WLAN only systems gives a lowe cost at fist aound 100 Mbps/km 2 (cc100). The multi-access concepts, WCDMA DCH o WCDMA HSDPA combined with g, ae seen to yield the lowest cost of the included subsystems. Howeve, the gain as compaed to, e.g., a single access WCDMA HSDPA system (with hieachical cell stuctues) is evident only at vey high taffic (> 300Mbps/km 2 ). With the models and assumptions used, thee is hence no significant multi-access cost eduction. On the othe hand thee is neithe any loss, and thee is thus no cc10 su g WCDMA DCH WCDMA HS DCH & 11g HS & 11g S3G S3G 450 4G 4G elay cc100 cc1000

5 cost dawback fo a mobile netwok opeato deploying maco and mico cells fist, and then adding WLAN only in hotspots, as compaed to a pue WLAN opeato. It may also be noted that HSDPA alone is a bette solution than both WCDMA DCH and g fo taffic loads up to 100Mbps/km 2. B. Futue Concepts The S3G concept, with simila coveage and cost chaacteistics as WCDMA DCH and HSDPA, also yield the same cost as these concepts at low and modeate taffic densities (while the systems ae coveage limited). S3G howeve emains coveage limited fo highe taffic densities, and yields lowe costs fo taffic densities exceeding 2Mbps/km 2. S3G is also seen to be a bette altenative than WCDMA HSDPA combined with g fo the full ange of studied taffic densities. The benefit of lage coveage is also seen fom the hypothetical S3G 450 system. Due to its lage cell adius, it yields cost almost 10 times lowe cost than the othe cellula concepts fo taffic densities up to aound 2Mbps/km 2. Even fo high taffic densities it is bette than standad S3G despite the same capacity pe AP. This indicates that despite a high mean taffic, thee ae lage aeas with less taffic whee a lage coveage pe AP is impotant. The peliminay 4G concept, without elaying, is seen to suffe somewhat fom its educed coveage fo taffic loads up to about 10Mbps/km 2. Beyond this level it yields the lowest cost pe use. The 4G concept with elaying povides slightly lowe cost than 4G without elaying fo modeate taffic densities, but still highe cost than both WCDMA and S3G. C. Picing Stategy and Sevice Offeing Consequences The cost pe data unit can be mapped to a cost pe use (and sevice) in seveal ways. This is a quite complex aea, which has been subject to many studies. Value based picing is, howeve, nowadays most often used in pactice and thee is typically little elation between pice and poduction cost [9]. Yet, the (incemental) poduction cost will tell if a sevice would be pofitable o not given the end use picing possibilities.. Assuming a taffic independent cost the aveage cost pe use is given by the total infastuctue cost divided with the numbe of suppoted uses. This can also be calculated by multiplying the cost pe unit data with the aveage pe use taffic intensity. Altenatively, assuming a linealy taffic dependent cost, the cost pe individual use is given by multiplying the cost pe unit data with the individual use taffic intensity. Seveal altenatives in between these extemes of couse exist. The esults pesented hee ae valid fo all these altenatives. An inteesting obsevation is that, with the models and assumptions used, the incemental infastuctue cost fo 1GB pe month pe use can be kept below 30 fo taffic densities exceeding about 0.2Mbps/km 2. Adding magins fo excluded costs (maketing, custome cae, coe netwok and sevice platfoms, pofit, taxes, etc.) about 1Mbps/km 2 is pobably a moe ealistic value. This oughly coesponds to a city cente aea with today s voice taffic, o a sububan aea with 40 times this taffic pe use. V. CONCLUSIONS The esults of this study indicate that, with the models and assumptions used, single-access solutions with high capacity maco cells yield the lowest costs pe use, despite a spatially non-unifom taffic demand. Examples of such systems ae WCDMA HSDPA and the peliminay S3G concept. Opeato deployed WLAN-only solutions yield high costs even if the equiement on factions of suppoted uses is small (20%). Except fo at vey high taffic, a multi-access netwok composed of WCDMA DCH o HSDPA maco and mico cells combined with IEEE g access points do not yield lowe costs pe use than using a single-access WCDMA DCH o HSDPA netwok consisting of maco, mico and pico cells. This is because seveal WLAN access points ae equied in each hotspot due to the poo coveage, which esults in an excess capacity and poo utilization of each AP. A hotspot concept with bette coveage could thus lead to bette esults also fo modeate aveage taffic densities. Fo mobile netwok opeatos having a 3G license intoducing WLAN hotspots hence need to be motivated by othe factos; such as access technology capabilities and spectum. Among the 4G concepts, it is seen that a simple elaying solution with maco-like elays nodes may yield impoved cost efficiency in aeas with modeate taffic demand, up to some 10s of Mbps/km 2. Fo taffic densities beyond this level, this paticula elaying solution is not motivated. The oveall lowest cost is enabled by a hypothetical high-capacity cellula system opeating in 450MHz spectum. This indicates the impotance of good coveage, which is of couse valid also fo altenative means to achieve it. Futue studies could make use of moe efined system and economical models. In paticula empiical data on taffic demand fo mobile data sevices would be useful to impove the heteogeneous taffic density model. REFERENCES [1] K. Johansson, et al., Relation between base station chaacteistics and cost stuctue in cellula netwoks, in the Poc. of IEEE Pesonal, Indoo and Mobile Communications (PIMRC), [2] F. Loizillon et al., Final esults on seamless mobile IP sevice povision economics, IST TONIC Deliveable no. 11, Oct [3] N. Niebet et al., Ambient Netwoks: An Achitectue fo Communication Netwoks Beyond 3G, in IEEE Wieless Communications, Vol. 11, Issue. 2, Apil 2004, pp [4] U. Gotzne et al., Spatial Taffic Distibution in Cellula Netwoks, in Poceedings of IEEE Vehicula Technology Confeence, [5] R. Ganesh and K. Joseph, Effect of non-unifom taffic distibutions on pefomance of a cellula CDMA system, Univesal Pesonal Communications Recod, Octobe [6] US Census Bueau, Table GCT-PH1. Population, Housing Units, Aea, and Density : 2000, available at [7] K. Johansson and A. Fuuskä, Cost efficient capacity expansion stategies using multi-access netwoks, in Poceedings of IEEE Vehicula Technology Confeence sping, [8] Thid Geneation Pateneship Poject (3GPP), RP , Poposed Study Item on Evolved UTRA and UTRAN, available at pp.og/ftp/tsg_an/tsg_ran/tsgr_26/docs/pdf/rp pdf. [9] T. T. Nagle and R. K. Holden, "The Stategy and Tactics of Picing", Second Edition, Pentice Hall, 1997.