Capacity and Coverage Analysis of Rural Multi- Radio Multi-hop Network Deployment using IEEE802.11n Radios

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1 IEEE th Malaysia International Conference on Communications (MICC) n 5th October Sutera Harbour Resort, Kota Kinabalu, Sabah, Malaysia Capacity an Coverage nalysis of Rural Multi- Raio Multi-hop etwork Deployment using IEEE8.n Raios lvin Ting, Davi Chieng an Kae Hsiang Kwong Wireless Communications MIMOS Berha Kuala Lumpur, Malaysia {kee.ting,ht.chieng,kh.kwong}@mimos.my bstract This paper presents the capacity an coverage performance analysis of a multiraio multihop network eployment using IEEE8.n raios for a typical rural area in Malaysia. Insights on the relationships between various key esign parameters particularly backhaul link rate, backhaul link istance/multihop istance, coverage size per / coverage size, number of MIMO spatial multiplex (SM) stream, number of per branch an effective capacity per access point or per user are acquire. Two optimization objectives namely ) to maximize coverage size an ) to maximize backhaul istance are introuce. Keywors-component; Wireless Mesh/Multihop etwork; Rural Deployment; IEEE 8.n; Backhaul I. ITRODUCTIO ccelerating broaban penetration an briging the igital ivie between rural an urban communities have long been one of the main agena of governments worlwie. Over the years, various initiatives have been launche in Malaysia to provie Internet access to the rural communities. More recently Ministry of Information, Communications an Culture an the Malaysian Communications an Multimeia Commission launche the Kampung WiFi initiative [], which aims to accelerate the national broaban penetration at the rural areas. ccoring to BI, the broaban access in rural areas shall inclue Basic Telephony ccess (via fixe an mobile networks), broaban connecte Community Broaban Libraries (CBLs) an Community Broaban Centres (CBCs). Motivate by the lacke of wire infrastructure in these areas, Wireless Mesh etwork (WM) has become a highly promising means to provie broaban access. s for the raio technology, IEEE8. WL or WiFi is naturally preferre ue to cost factor an wie sprea market aoption. Over the years WM technologies, particularly those base on WiFi raios, have evolve from single raio systems to multiraio systems involving heterogeneous raio interfaces such as IEEE8.a, b, g an n. The most commonly known inustrial practice aopts the architecture which comprises of IEEE8.a raios at the backhaul an IEEE8.g for the access. This is largely motivate by the fact that IEEE8.a has more non overlapping channels an much less congeste spectrum ban. lthough WM offers a wie range of benefits, it continues to suffer capacity limitation ue to excessive sharing of capacity as the number of hop increases. To this en the recently approve IEEE 8.n stanar which offers physical ata rates up to 6Mbit/s an higher resiliency towars interference via MIMO technology may change the perception to a certain extent. To ate there are alreay a wie range of n-base wireless mesh/multihop network proucts an solutions in the market. However, the performance of such network is not well unerstoo especially from the capacity an range (coverage) viewpoints. In particular this paper aims to unerstan the relationships between various key esign parameters such as backhaul link rate, backhaul link istance/multihop istance, coverage size per / coverage size, number of MIMO spatial multiplex (SM) stream, number of per branch an effective capacity per access point which can later be translate into ata rate per user using IEEE8.n raios. The stuy takes into consieration the unique characteristics in rural eployments, i.e. istribution of the users is rather concentrate like a hotspot but istribute. Unlike the urban case, the istance between hotspots may range from hunres of meter to tens of km (between villages). lso unlike the urban zones, contiguous coverage is not require. Fig. provies a snapshot of a typical rural eployment in Malaysia. Branch Branch Branch Figure. Case Stuy: Kampung (village) Ulu Dusun, Sabah, Malaysia.*courtesy of Google Maps. We first, we evelope an analytical moel that inclues physical layer, mac layer an propagation moel to evaluate the capacity an coverage for a multi-raio multihop infrastructure network.. In this moel, access raio an //$6. IEEE 77

2 backhaul raio are consiere to operate in two ifferent frequencies an not interfering to each other. Inter relationship between coverage an capacity between access an backhaul planes is then erive. Base on the moel, we apply the greey algorithm to fin the optimal coverage or backhaul istant for the consiere multihop network. The reminer of this paper is organize as follows. ext section iscusse on the relate works. Section an 4 presents the assumptions an system moel respectively. Results are iscusse in section 5 an finally the conclusions an future work is rawn in section 6. II. RELTED WORKS Rural WM eployments both large an small, especially those base on WiFi raio have been wiely reporte worlwie. [] offers an insightful stuy on eploying a rural long istance mesh network in the Scottish Highlans an Islans using IEEE8.a backhaul an b/g access in the 5GHz an.4ghz bans respectively. In this work, two key aspects are stuie namely effect of water level on long istance links an the practicality of using energy sources beyon solar. [] eploye a WM in the village of Wray, Englan that aime at proviing Internet service to the community. The stuy shares their experiences which cover a wie range of issues from both technical an social aspects. similar initiative was unertaken in Macha village, Zambia that focuses entirely on proof of concept an investigation into a wie range of issues covering social, geographical, economic, business moels an sustainability on top of technical challenges [4]. From their eployments in Digital Gangetic Plains an shwini, [6] presents their experiences an insights on network planning, MC protocol enhancements, network management, power savings, applications an services. eployment of a similar nature as to the above was reporte in [5] but limite to experience gaine from commercial single raio b/g noes. To the best of our knowlege no existing work provies WM capacity an coverage analysis using IEEE8.n raios with aim to unerstan the relationships between various key esign parameters liste in the previous section. III. SSUMPTIOS. rchitecture The architecture consists of many Multiraio ccess Routers (s) that are interconnecte via backhaul raios to form a mesh network. Here it assume that all the traffics flow in multi-hop fashion between s an the Gateway (GW) noe, which has the access to the core network. The basic architecture is illustrate in Fig. as follows: 5GHz.4GHz With access Without access.4ghz Figure. Multiraio Multihop rchitecture.4ghz GW From this basic architecture, ifferent topologies as shown in Fig. can be forme. B. Topology Formation n area of.5 square km (.5x.5 km) of a village calle Kampung Ulu Dusun as epicte in Fig. is selecte for our stuy. It can be observe that houses are not uniformly istribute in this village an they ten to group in some specific areas such as near to the main roas. We call a group of houses as a cluster an there are several clusters in the area. s are eploye in the centre of those clusters to provie strongest raio signal to most of houses. In, only 9 s (incluing gateway) are require to provie full coverage with an average of 5 houses covere by each. ll s are assume to be eploye outoor an the evices are receiving the signal inoor. lso shown in Fig. there are three main branches. Each branch forms a simple chain or tree topology with, an 5 s respectively. (a) GW (b) s () 4 s backhaul link istance Possible topology with any aitional imme MR to make up 5 MRs in (c) s access coverage cell with multiple MCS (e) 5 s (ue to limitation of the space, not all scenarios are shown) Figure. Possible topologies with ifferent number of per GW The otte lines inicate the possible alternative links that transform a multihop into mesh. From capacity viewpoint, a mesh network is assume to behave like a multihop tree when the whole network is operating at maximum loa. In other wors the alternative paths merely provie resiliency an loa 78

3 balancing but not aitional capacity []. lso since we assume that all s provie access, the terms an access cell shall be use interchangeably in the following sections. C. User Distribution an Traffic ssumption Even though users are istribute sporaically across the whole eployment area, users are assume to be uniformly istribute within the raio cell. The coverage size per cell is ecie by two factors. Firstly, we nee to make sure that the capacity of the MR is sufficient to support all users for a chosen coverage size. Otherwise, a smaller coverage size is neee. Seconly, the coverage is etermine by the transmission range of the esire MCS that meets the target ata rate to be supporte at the cell ege. Target ata rate per user represents the maximum ata rate (uplink an ownlink) that can be enjoye by each en user. This is representative of the connection spee (or healine spee) typically avertise by a network operator. Since WiFi raio is the focus of this paper, we therefore only consier a generalize capacity. The overbooking factor is the ratio of the potential maximum eman to the actual banwith consume. Typically the overbooking factor ranges from 5: to : [] where factor of 5 or 4: is usually associate with web browsing application. In other wors, the lower the factor, the higher the average banwith or QoS eman for that service. D. Interference Base on the observations foun in [], [7] an [8], interferences resulting from external WiFi or non WiFi transmitters are minimal an even non-existence in some cases in rural environment. This leaves the major contribution of interference by own networks in form of co channel. Such interference can be mitigate via careful channel planning an irectional antenna orientation, which is can be a pretty straightforwar task ue to wie availability of non-overlapping channels in the 5GHz backhaul. IV. SYSTEM MODEL. Capacity Per User an Per Calculation of average capacity per user within a is base on equation []: () Cuser = MCS user, i i = Reff, i Where user, is number of users in specific Moulation an i Coing Scheme (MCS) zone i,, is the effective ata rate of the MCS zone an is the number of MCS consiere., is efine by:,, () Where is the link efficiency an, is the raw physical ata rate given by MCS type i. For the calculation of mean capacity per user, it is assume that the time of packet transmission is inversely proportional to the access link spee. Therefore, for the packets of the same size, users in high ata rate zone will occupy less air-time than users in lower ata rate zone so that equal capacity can be istribute to all users to achieve fair capacity sharing. Hence, the effective capacity per is simply the prouct of mean capacity per user an number of users covere by the : () ssuming s can simultaneously transmit (or receive) traffic to each of its neighbouring s as well as to its own users, the maximum mean capacity per MP is then limite by the first hop link capacity, : max (4) Where is the number of per branch. In this stuy, we assume that the rural houses were mainly mae of thick woo which incurre a wall penetration loss of.69b accoring to [4]. s for the propagation moel, the free space path loss moel is aopte an given in equation 4: ( log ( ) + ) + log ( ) 47 PLpropagatio n = α f (5) Where α is the propagation coefficient, is the istance in kilometres an f is the carrier frequency in hertz. The IEEE8.n stanar is use to represent WiFi an its receiver sensitivity is obtaine from [5] an the values per MCS are tabulate in TBLE I. The general link buget is given in eqn 5. PL = EIRP R + G FM L (6) max sen rx wall Where PL max is link buget in B, EIRP is the effective isotropic raiate power, G rx is the receiver antenna gain, FM is fae margin in B, R sen is the receiver sensitivity an L wall is the wall penetration loss in B. For backhaul link, wall loss is set to zero an 8B fae margin is consiere instea to ensure link availability of 99.9% as accoring to [6] base on rayleigh faing moel. TBLE I. MCS D RECEIVER SESITIVITY 8.n Receiver MCS Sensitivity (Bm)[5] Type Inex(i) MHz 4MHz BPSK / QPSK / QPSK / QM / QM / QM / QM / QM 5/ B. Optimization First Hop BH Optimisation lgorithm Begin Define MCS supporte by where i,, Where i= is highest orer MCS type consiere an J is the lowest orer MCS consiere (typically at the ege of cell) Repeat Step : Fin the coverage are of MCS type i,,,.., i= i= (refer TBLE I) i = J 79

4 ,, where is coverage raius of MCS type i Step : Fin the number of users supporte in coverage area J i i ρ user = = where is the user ensity Step : Fin effective capacity per using equation Step 4: Fin aggregate capacity requirement for all s at first hop: C C eff, hop = eff, Where: is the number of mesh noes per branch, = -5 noes in this stuy Step 5: Map s capacity requirement to first hop BH link an select BH with maximum istance that support s capacity requirement. Maximum BH istance is chosen by selecting BH where: Min{ C BH C eff,hop } an BH Distance =, if C BH < C eff,hop ; MCS Types Until meeting lowest MCS, J En Greey BH Distance Optimisation lgorithm (maximizing multiple hop istance) Begin, initial number of or coverage cell., initial backhaul istance, initial coverage size max max( ) hop ; //erive max st hop BH istance = 5 per = 5 ( max ) ; //erive corresponing coverage area size per 5 *5 = repeat per ( ) ; //fin corresponing BH istance //correspon to max coverage + + until number of is fulfille En Greey Coverage Optimisation lgorithm Begin, initial number of, initial backhaul istance, initial coverage size per per max max ( ); //erive max coverage per, 5 = 5 s per max *5 repeat per ( max ) ; //fin corresponing BH istance //correspon to max coverage + + until number of s is fulfille En. General Parameters V. RESULTS D LYSIS Table II summarizes the parameters use use in the stuy. TBLE II. RDIO D EVIROMETL PRMETERS Parameters Units n 4MHz (Backhaul) n 4MHz (ccess) Receive antenna gain B 5 RF frequency GHz Channel banwith MHz 4 Transmit EIRP power Bm 7 Link layer efficiency( ).5.5 Propagation Coefficient. (LOS).6 (rural) Margins/Loses Interference B Faing B 8 8 Wall Penetration Loss B -.69 User Requirements Overbooking Factor - : Data Rate Mbps -,, 5, User Density user/sqkm - The EIRP limits use are base on the guieline given by Malaysian Communications an Multimeia Commission. In this stuy the effective capacity represents the IP layer throughput where in most cases is approximately 5% of the raw PHY ata rate. The overbooking factor is set at : to represent higher banwith applications such as vieo streaming or FTP type applications. User ensity is erive from the selecte scenario in Fig.. B. Effective Capacity vs. Distance Fig. 4 shows the ieal effective capacity of a MR s backhaul an access link versus istance in km when 4 spatial streams are use. Effective Capacity (Mbps) Backhaul, 4 Stream Distance (km) ccess, 4 Stream Figure 4. Effective capacity of IEEE8.n vs. istance s shown, ue to the usage of high gain antenna an maximum EIRP limit, the backhaul link can reach almost km an up to 4m for access coverage raius using the most robust (lowest orer) MCS. s for the access, this is only true if 8

5 there are four antennas at the user en which is unlikely to be the case in practise. C. First HopBackhaul Distance vs. Coverage vs. User Data Rate with Different umber of per Branch Fig. 5 shows that with - branch case (branch ), the first hop backhaul link can support up to.4sqkm of coverage cell size with the maximum istance between s equal to.9 km when user ata rate is Mbps. When user ata rate is increase to Mbps, the maximum coverage size.4sqkm can no longer be supporte at the same backhaul istance. slightly smaller coverage size per (.6sqkm) has to be tolerate. When the user ata rate is further increase to 5 an Mbps, several coverage sizes can no longer be supporte. For the Mbps case, backhaul istance is reuce to.8 km to support coverage size of. sqkm. Smaller coverage implies no service for some users. Fig. 7 shows that the ate rates of,, 5 an Mbps can still be supporte by branch but with much reuce coverage size. D. Backhaul Distance/Coverage Maximization In this section we aopte the backhaul istance (or coverage size) maximization algorithm on the 5- branch (branch ) an the result is presente in Fig. 8 an 9. Figure 5. Backhaul istance vs. coverage size vs. user ata rate for - branch using spatial stream at backhaul link (refer branch in Fig.) Fig. 6 shows for the - branch case (branch ), similar tren as in - case is observe but with noticeable reuction in coverage size an backhaul link istance per user ate rate. From the result, we can euce that Mbps can be supporte by branch provie the cell size is not more than.sqkm. Figure 6. Backhaul istance vs. coverage size vs. user ata rate for - branch using spatial stream at backhaul link. (refer branch in Fig.) Figure 7. Backhaul istance vs. coverage size vs. ata rate for 5- branch using spatial stream at backhaul link (refer branch in Fig.) Fig. 8 shows that the (aggregate) coverage size achievable against various ata rate using the greey algorithm. It can be observe that the 5- branch network can support more than sqkm of aggregate coverage size with Mbps per user. Fig. 9 shows that the maximum multihop backhaul istance (aggregate) remains constant at ~4km for all ata rates an number of spatial streams consiere. In this case, the coverage size is being trae off with backhaul istance. It is also clearly shown that higher number of spatial streams enable bigger coverage sizes. Total Coverage for 5 s (sqkm) 5 Stream Stream Stream 4 Stream Figure 8. Total coverage size of 5- branch with maximise BH istance Fig. shows coverage size an backhaul istance with coverage size being optimize by the greey algorithm. Maximum achievable aggregate coverage size for 5- branch is. square km. For high capacity 4 spatial-stream backhaul, the coverage size can be maintaine by increasing the user ata rate with no more than one fifth of loss in coverage when proviing Mbps ata rate per user. Capacity limite spatial-stream backhaul performs the worst in maintaining coverage size when user ata rate increases. The aggregate 8

6 coverage size of Mbps is aroun 7% smaller than coverage size of Mbps. s shown in Fig. the backhaul istance rops graually when user ata rate increases. It is reuce by almost % with Mbps as compare to Mbps user ata rate. Multihop Backhaul Distance (km) Stream Stream Stream 4 Stream Figure 9. Total backhaul istance for 5- branch with maximise BH istance Total Coverage for 5 s (sq km) 5 Stream Stream Stream 4 Stream Figure. Total coverage size of 5- branch with maximise access coverage size Multihop Backhaul Distance (km) Stream Stream Stream 4 Stream Figure. Total backhaul istance for 5- branch with maximise access coverage size Since the backhaul istance optimization algorithm tens to stretch for longer istance by traing off coverage size, less number of users can therefore be supporte. This algorithm is more suitable for rural eployment where the number of user is low an istribute. The aitional istance provie on backhaul enables a great egree of freeom in terms of placing. On the other han, the coverage maximization algorithm which ultimately converges towars blanket type coverage is believe to be more suitable for urban or suburban eployments. VI. COCLUSIOS This paper presents a capacity an coverage analysis of a multiraio multihop network eployment using IEEE8.n raios for a typical rural area. Insights on the relationships between various key esign parameters particularly backhaul link rate, backhaul link istance/multihop istance, coverage size per / coverage size, number of MIMO spatial multiplex (SM) stream, number of per branch an effective capacity per access point or per user have been acquire. In general, user ata rate ranging from to Mbps can be supporte with a 5-hop multiraio network using IEEE8.n raios with some traeoffs in terms of maximum coverage size. We have also introuce two approaches that maximize the coverage size or backhaul istance respectively. s expecte, the backhaul istance maximization algorithm is more suite for rural case an coverage maximization on the other han is more appropriate for urban or suburban eployments. REFERECES [] KMPUG WIFI TO CCELERTE EFFORTS FOR THE TIOL BRODBD IITITIVE (BI), Press Release, Mihttp:// _Julau_Sarawak_79.pf [] G. Bernari, P. Buneman, an M. K. Marina, Tegola Tiere Mesh etworktestbe in Rural Scotlan,in WiS-DR 8, San Francisco, C, Sept. 8. [] Ishmael, J., Bury, S., Pezaros, D., Race,.: Rural community wireless mesh networks. In IEEE Internet Computing, Vol., Issue 4, 8, pp. 9. [4] K. W. Matthee et. al., Bringing Internet Connectivity to Rural Zambia Using a Colloborative pproach. In Proc. n IEEE/CM ICTD, Bangalore, Inia, Dec. 7. [5] D.L. Johnson, Evaluation of a single raio mesh network in South frica, in ICTD 7, Bangalore, Inia, Dec. 7. [6] B. Raman an K. Chebrolu, Experiences in using WiFi for Rural Internet in Inia, in IEEE Communications Magazine, Vol: 45(), Jan 7. [7]. Sheth et al, Packet Loss Characterization in WiFi-base Long Distance etworks, In Proc. IEEE IFOCOM 7, laska, May 7, [8] D. Gokhale, S. Sen, K. Chebrolu, an B. Raman, On the Feasibility of the Link bstraction in (Rural) Mesh etworks, In IFOCOM 8, Phoenix, Z, US, pr. 8. [9] Utpal Kumar Paul, Riccaro Crepali, Jeongkeun Lee, Sung-Ju Lee, Raul Etkin, Characterizing WiFi Link Performance in Open Outoor etworks, To appear in IEEE SECO, Utah US, June. [] Matthias Lott, I. Forkel, Multi-Wall-an-Floor Moel for Inoor Raio Propagation, in IEEE VTC Spring, Page vol., May, Phoes, Greece. [] Kaveh Pahlavan an llen H. Levesque, Wireless Information etworksn Eition, 5 Wiley Interscience. []. Ting an D. Chieng, Design an Capacity Performance nalysis of Wireless Mesh etwork, in Mobility 8, Ilan, Taiwan, Sept. 8. [] D. Chieng, D. V. Hugo,. Banchs, Cost Sensitivity nalysis for Carrier Grae Wireless Mesh etworks with Tabu Optimization, Workshop of Carrier Grae Wireless Mesh etwork, in Proceeing of IEEE IFOCOM, San Diego, California, March. [4] Mohamme, Y.E, ballah,.s. an Liu, Y., Characterization of Inoor Penetration Loss at ISM Ban, in CEEM, 4-7 ov. [5] Datasheet: Unex DM-9: 8.n a/b/g wifi x mini-pci moule, MB9/R9. [6] Wireless Link Buget nalysis, How to Calculate Link Buget for Your Wireless etwork, Tranzeo Wireless Technologies Inc, 8