Aalborg Universitet. Published in: Vehicular Technology Conference (VTC Fall), 2013 IEEE 78th

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1 Aalborg Unverstet Modelng of W-F IEEE ac Offloadng Performance For 1000x Capacty Expanson of LTE-Advanced Hu, Lang; Sanchez, Mara Laura Luque; Materna, Mchael; Kovacs, István Zsolt; Vejlgaard, Benny; Mogensen, Preben Elgaard; Taoka, Hdekazu Publshed n: Vehcular Technology Conference (VTC Fall), 2013 IEEE 78th DOI (lnk to publcaton from Publsher): /VTCFall Publcaton date: 2013 Document Verson Accepted author manuscrpt, peer revewed verson Lnk to publcaton from Aalborg Unversty Ctaton for publshed verson (APA): Hu, L., Sanchez, M. L. L., Materna, M., Kovacs, I. Z., Vejlgaard, B., Mogensen, P., & Taoka, H. (2013). Modelng of W-F IEEE ac Offloadng Performance For 1000x Capacty Expanson of LTE-Advanced. In Vehcular Technology Conference (VTC Fall), 2013 IEEE 78th (pp. 6). IEEE. I E E E V T S Vehcular Technology Conference. Proceedngs, DOI: /VTCFall General rghts Copyrght and moral rghts for the publcatons made accessble n the publc portal are retaned by the authors and/or other copyrght owners and t s a condton of accessng publcatons that users recognse and abde by the legal requrements assocated wth these rghts.? Users may download and prnt one copy of any publcaton from the publc portal for the purpose of prvate study or research.? You may not further dstrbute the materal or use t for any proft-makng actvty or commercal gan? You may freely dstrbute the URL dentfyng the publcaton n the publc portal? Take down polcy If you beleve that ths document breaches copyrght please contact us at vbn@aub.aau.dk provdng detals, and we wll remove access to the work mmedately and nvestgate your clam. Downloaded from vbn.aau.dk on: July 06, 2018

2 Modelng of W-F IEEE ac Offloadng Performance For 1000x Capacty Expanson of LTE-Advanced Lang Hu (1,2) Laura Luque Sanchez (1) Mchal Materna (3) István Z. Kovács (4) Benny Vejlgaard (4) Preben Mogensen (1,4) Hdekazu Taoka (2) (1) Department of Electronc Systems, Aalborg Unversty Aalborg, Denmark (2) DOCOMO Communcatons Laboratores Europe - Munch, Germany (3) Noka Semens Networks - Wroclaw, Poland (4) Noka Semens Networks - Aalborg, Denmark Abstract Ths paper studes ndoor W-F IEEE ac deployment as a capacty expanson soluton of LTE-A (Long Term Evoluton-Advanced) network to acheve 1000 tmes hgher capacty. Besdes ncreasng the traffc volume by a factor of x1000, we also ncrease the mnmum target user data rate to 10Mbt/s. The objectve s to understand the performance and offloadng capablty of W-F ac at 5GHz. For the performance evaluaton of W-F, we propose a novel analytcal throughput model that captures both key ac enhancements and mult-cell nterference. We provde a quanttatve evaluaton of large-scale ndoor W-F ac deployment n a real urban scenaro by extensve smulatons. We conclude that deployng ndoor W-F access ponts n almost every buldng s essental to carry the x1000 traffc volume and ensure a mnmum user data rate of 10Mbt/s. I. INTRODUCTION Moble network operators are facng a crtcal challenge on how to deal wth the antcpated moble data exploson of 1000 tmes more traffc wthn the next 10 to 15 years [1] n a cost effcent way. Increased use of smartphones, tablets, netbooks and USB stcks wth embedded HSPA (Hgh Speed Packet Access)/LTE (Long Term Evoluton) capabltes wll be contnuously taxng the moble networks for scarce capacty resources. Fortunately, most of these portable devces also have embedded W-F access capabltes. To accommodate the hgh expected moble traffc growth, ndustry and academa have started researchng how to expand the network capacty: The capacty cube of mproved spectrum effcency, allocaton of more spectrums at hgher frequency and deployng more and smaller cells are generally antcpated as the methods to ncrease network capacty. Dfferences n vews are more n the detals of how much capacty gan s expected from each doman of the capacty cube [2][3]. On top of the x1000 traffc volume ncrease over the next years, we also expect the mnmum user data rate to ncrease by a factor of x10. In practce our recent network evoluton studes ndcate that the most cost effcent network evoluton wll be a Heterogeneous Network (HetNet) confguraton. Among the possble HetNet capacty enhancement paths, W-F offloadng s becomng an essental and attractve ngredent: 1) W-F operates on excessve unlcensed spectrum (2.4GHz/5GHz band) and may provde great capacty enhancement at a much lower cost, compared to cellular-based small cell optons (mcro and pco cell) that operate on lcense band; 2) W-F has been a mature technology, and 2.4GHz W-F access support s embedded n most data enabled moble devces e.g. smartphones, tablets and laptops. These form a very good bass for deployng advanced W-F offloadng soluton; 3) The W-F standard development s contnuously evolvng wth IEEE n today beng manstream and the latest hgh capacty ggabt W-F soluton IEEE ac [4] soon reachng the commercal market. Most mportant n the evoluton s probably the support of the 5GHz ISM band unleashng approxmately MHz of new spectrum for wreless usage. In ths paper, we provde a quanttatve study on the potental role of ndoor W-F ac deployment as a HetNet soluton for a LTE-A network expanson to acheve 1000x more capacty. We base our study on a European Cty case study usng exstng macro stes, 3D-buldng models and spatal traffc measurements and modelng. Our contrbutons are two-fold: frstly, we propose an analytcal W-F throughput model that captures key ac features and mult-cell nterference; secondly, we quanttatvely study the performance and offloadng potental of ndoor W-F ac deployment to acheve 1000x more capacty. The remander of the paper s organzed as follows: Secton II presents the ac modelng framework. Secton III ntroduces the system model of deployment study ncludng LTE-A network model. Secton IV presents W-F deployment strateges. Secton V provdes performance results. Fnally, Secton VI concludes the paper. II. IEEE AC MODEL A. Key Features of W-F IEEE ac IEEE ac can be seen as a capacty evoluton of IEEE n standard ac supports medum access control () layer throughput of more than 500 Mbps for a sngle user scenaro and aggregated throughput of more than 1 Gbps for a mult-user scenaro. Four basc notons are enhanced: wder channel bandwdths, hgher-order modulaton codng scheme (MCS), support of dynamc channel wdth capablty, and mult-user multple nput multple output

3 (MU-MIMO). Compared to n standard, a wder bandwdth of 80 and 160 MHz s ntroduced n ac e.g. the 80 MHz mode uses two adjacent 40 MHz channels wth some extra subcarrers to fll the unused tones between two adjacent 40 MHz channels. Also, two new MCSs 8 and 9 are ntroduced based on 256-QAM wth codng rates of 3/4 and 5/6 for a further 20% and 33% mprovement n a physcal layer data rate respectvely, compared to the hghest MCSs 64-QAM wth 5/6 codng rate of n. Thrdly, ac modfes the n to address coexstence and medum access wth the support of wder channels, where the staton can dynamcally adjust ts channel bandwdth dependng on ts neghborng cell nterference stuaton. Fnally, ac ntroduces downlnk MU-MIMO where an access pont can smultaneously transmt data streams to multple clent statons. B. Physcal Layer Performance Model We model the physcal layer performance of ac by usng sgnal to nterference plus nose rato (SINR) to physcal throughput mappng curve. Ths curve s obtaned by usng exponental effectve SINR method (EESM). C. Throughput Model The achevable layer throughput can be estmated by modelng ac dstrbuted coordnaton functon (DCF) under multple W-F cells (or Basc Servce Sets) coexstence scenaro. Each staton (STA) proactvely contends the channel access wth other statons and access pont (AP) usng the protocol of Carrer Sense Multple Access/Collson Avodance (CSMA/CA). The rado resource allocaton s fully dstrbuted and mplctly done by all nodes wthn the same cell followng the same channel access protocol. It s nodecentrc n the sense that the AP has the same channel access chance as each STA. There are two essental aspects of modelng ac DCF functon: 1) effcency: the dstrbuted channel access of CSMA/CA leads to sgnfcant protocol overhead as well as collsons; The effcency measures the overall channel usage for actual data transmssons despte the overhead; 2) Interference: neghborng co-channel APs and STAs generate strong nterference so as to prevent the CSMA/CA-based channel access n current cell; In partcular, a node s prevented from sendng packets to other nodes when t receves nterference sgnal from a neghborng transmtter wth the receved sgnal strength level (RSSI) larger than a sensng threshold. The throughput of user can be modeled as follows: Tput = RB BW ) (1) ( Where effcency:, channel bandwdth: BW, spectrum effcency of user :, rado resource share of user : RB. The product of BW and s the effectve channel bandwdth despte the protocol overhead. BW and are known parameters. Frstly, effcency can be modeled by usng method n [5]. Defne frame transmsson tme: T T data, ACK frame transmsson tme: ACK, back-off tme: T backoff and the mean value of back-off tme: E T ). SIFS (Short Inter- ( backoff Frame Space) and DIFS (Dstrbuted Inter-Frame Space) tme ntervals are defned as W-F standard. We assume that Aggregaton- Protocol Data Unt (A-MPDU) s the frame aggregaton opton wth mplct block acknowledgement (.e. ACK frame s equal to BA frame) [4]. We also assume that the frame sze s fxed and equal to the aggregated sze by usng A-MPDU. effcency s: Tdata T SIFS T DIFS E( T ) ave (2) s average spectrum effcency of all nodes ncludng both STAs and AP. Next, to derve RB n eq.(1), we assume the followng: each user generates both downlnk (DL) and uplnk (UL) traffc at the same tme, and there are N STAs n one cell; To model the asymmetry load of DL and UL, we assume that DL has fullbuffered traffc model, whereas UL traffc has full-buffer model wth an actvty factor (between 0 and 1). In other words, AP always has DL frames to transmt and always contends channel access, whereas each STA only contends channel access wth a probablty to transmt UL frames. Assume that M neghborng APs and STAs create nterference to the servng W-F cell, they are modeled as M addtonal STAs n the same cell that contends for the channel access. RB n eq. (1) can be derved by usng a set of propertes of CSMA/CA protocol [8] under full-buffered traffc model :1) In the long term, the UL and DL rado resource share rato s N for each STA. When =1, UL traffc has N tmes hgher ar nterface tme than the DL traffc at each STA, snce AP only has the same ar nterface tme as one STA, but t has to serve all N STAs by sendng DL traffc; 2) In the long term, a set of STAs receve the same amount of DL data, ndependent of ther spectrum effcency. The same property apples to UL. STA wth hgher spectrum effcency wll occupy less ar nterface tme than lower spectrum effcency STA. Thus the set of STAs of the same W-F cell have the same average DL throughput n the long term, ndependent of ther SINR; The same appled to the UL throughput; Defne the frame sze to be a fxed value of Pkt, the overall DL throughput of STA can be derved as follows : Tput DL where T data data ( N 1) Ave k 1.. N ack _ Frame _ sze Pkt Pkt k j1,2... M ( BW The UL throughput of STA can be derved n a smlar way. D. Model Valdaton From System-level Smulaton The analytcal throughput model s valdated va system-level ac smulatons. We assume the followng: t s a sngle W-F cell scenaro; each STA has the same DL/UL SINR of 10.8 db; channel access probablty s 1/20 and A-MPDU by aggregatng 40 frames of 1500 bytes each; SISO antenna confguraton wth channel bandwdth of M backoff Pkt j (3) )

4 Ave Tput (Mbps) 20MHz. Fg.1 shows the DL and UL throughput per STA vs number of STAs. The analytcal model matches well the system-level smulaton result as shown n fg.1. In partcular, as the number of STAs ncrease, DL/UL throughput scales down wth the followng factor: DL scalng factor: 1 (4) N ( N 1) UL scalng factor: 1 (5) N 1/ Assume that β s constant, as N ncreases, DL throughput decreases much faster (n O (N N)) than UL throughput (n O (N)) Sngle WF BSS, Each STA has DL/UL SINR= 10.8 db, UL/DL Rato=1/20, SISO, BW=20 MHz ac DL Model ac UL Model ac DL Sm ac UL Sm Number of STAs Fg ac DL and UL Throughput III. REAL DEPLOYMENT SCENARIO MODELING A. LTE-A Network Layout & Buldng Database The W-F ac deployment study has been carred out n a dense urban scenaro wth a deployed LTE-A network that s upgraded from the exstng 3G macro ste locatons (descrbed n [5][6]). The sze of the nvestgated area s approxmately 1 km 2, contanng 4 three-sector macro stes wth optmzed antenna down-tlt and average nter-ste dstance of ~300 m. In addton, there are 40 outdoor mcro cells deployed n traffc hotspot area to help offloadng the macro cell. The number of mcro cells deployed corresponds to the optmal number n terms of rado performance and cost, under practcal constrants. The real 3D buldng database of the nvestgated area s employed for modelng ndoor area. The entre area of 1 km 2 contans 1000 buldngs wth 5 floors n average. The same cellular rado performance model as n [6] s employed. The LTE-A physcal layer performance s modeled by a SINR-to- Physcal_Throughput mappng curve that ncludes adaptve modulaton and codng (AMC), hybrd automatc repeat request (HARQ) and multple nput and multple output (MIMO) transmsson up to 2x2 spatal multplexng, whereas the user outage mnmzaton scheduler s employed for rado resource allocaton [5][6]. B. Spectrum Allocaton β = 1/20 For the reference network setup, we assume that the several lcensed spectrum bands used by current 2G and 3G network layers are re-farmed for our LTE-Advanced/4G-lke network. In partcular, each of the 12 LTE-Advanced macro cell sectors s assumed to employ 4 dfferent carrers, operatng n FDD (Frequency Dvson Duplexng) mode at 800 MHz, 900 MHz, 1800 MHz and 2100 MHz carrer frequency and use deal LTE-Advanced carrer aggregaton (CA) between the MHz bands and smlarly between MHz bands. As the basc confguraton, the mcro cell layer s assumed to operate n the FDD 2.6 GHz band. In addton, the new 3.5GHz spectrum that s beyond Internatonal Moble Telecommuncatons (IMT) spectrum [9] can be allocated to enhance the mcro cell performance. We assume that the 3.5GHz spectrum s used n TDD (Tme Dvson Duplexng) mode, snce t gves more flexblty on both dynamc downlnk/uplnk traffc rato and more flexble spectrum rearrangement. We assume the TDD downlnk/uplnk rato s 1:1. To further enhance the network capacty and ndoor coverage, we look nto the deployment of ndoor W-F ac APs operatng at unlcensed 5 GHz band. C. 3D Propagaton Modelng To accurately estmate path loss for macro and mcro cells at outdoor locatons, a 3-D ray-tracng tool s used. Outdoor to ndoor path loss s predcted by usng a 20 db external wall loss plus a lnear attenuaton factor of 0.6 db/meter for ndoor nternal wall loss [5][6]. The studed area was dvded n square pxels of 10 x 10 meter, whch are the basc unt for the performance modelng and evaluaton [5][6]. In order to accurately model the ndoor small cell deployment, the 3-D buldng footprnt and ts number of floors are consdered n the modelng framework along wth a statstcal outdoor-to-ndoor and ndoor-to-ndoor path loss models (followng the descrpton n [5][6]). D. Network Key Performance Indcator The selected network key performance ndcator (KPI) s defned as the 90% servce coverage for a gven fxed mnmum downlnk user data rate,.e. less than 10% outage. We estmate that the current mnmum downlnk data rate requred for the subscrbers to experence an 'acceptable' moble broadband servce s n the order of 1 Mbt/s [2]. We expect ths mnmum acceptable downlnk data rate to reach 10 Mbt/s durng the tme frame of the 1000x traffc growth/ 1000x capacty demand [2]. E. Spatal Traffc Model & 1000x Traffc/Capacty Demand The network traffc load s smulated n terms of the number of smultaneous actve downlnk users, whch are randomly placed n the network area followng a predetermned spatal user densty map. Ths spatal user densty map s derved from busy hour downlnk traffc measurements n the exstng 3G network. We have combned ths measured spatal traffc data wth an expected outdoor-ndoor traffc splt of 30-70% and a traffc dstrbuton across the buldng floors wth 50% of the ndoor traffc generated at ground floor [5][6]. The relatve spatal user densty dstrbuton s assumed to reman constant durng the tme perod of the 1000x traffc growth. By usng our traffc forecast tool [7], the 1000x traffc/capacty demand s modeled n terms of an ncreased number of smultaneous actve users downloadng data n the network as follows: smultaneously actve downlnk users wth 10 Mbt/s mnmum user data rate requrement.

5 IV. WI-FI DEPLOYMENT STRATEGIES Ths secton descrbes W-F deployment n terms of traffc steerng, mult-channel operaton and access pont placement. A. Traffc Steerng Methods There are two optons of the traffc steerng between W-F network and LTE-A network: 1) Best-Server: the user s frst connected to the W-F network f ts SINR s larger than a certan threshold.e. 5 db; the user selects the AP that gves the best SINR; users are offloaded to W-F network as much as possble wthout consderng actual user experence; 2) SMART: the user frst connects to W-F network only f 1) User SINR > threshold; 2) Estmated user throughput > mnmum data rate. B. Mult-channel Operaton ac operates on 5GHz unlcensed spectrum wth 480MHz bandwdth ac has the flexblty of confgurng varous channel bandwdth,.e. ncrease the channel bandwdth by bondng multple adjacent channels. The total 480 MHz spectrum can be channelzed nto varous bandwdth optons 20/40/80/160MHz, whch result n 24/12/6/3 numbers of orthogonal channels that can be allocated to each W-F cell to mtgate nter-cell nterference. The smaller the bandwdth, the larger number of orthogonal channels can be allocated to mtgate nter-cell nterference. For the channel allocaton, we assume a smple and effcent unform channel assgnment: each W-F cell s assgned one channel that s unformly pcked up from the channel pool. C. Access Pont Placement Due to the expected hgh number of W-F APs nvolved, the AP placement algorthm s based on a smple traffc-drven deployment algorthm [5][6]. The man dea s that of subdvdng the nvestgated area nto spatal grds, sortng the aggregate traffc densty of each grd, and fnally deployng APs n the hghest traffc densty grds. V. PERFORMANCE EVALUATION In ths secton we provde the numercal results and the performance of ndoor W-F ac deployment. Frstly, we study the W-F AP densty and 3.5GHz spectrum allocaton to outdoor mcro cell n order to meet 1000x capacty demand. Secondly, we study varous W-F deployment strateges.e. traffc steerng polces and channel bandwdth optons, and dentfy the optmal confguratons. The descrbed modelng framework of W-F ac and LTE-A cellular network has been mplemented n a MATLAB-based network plannng tool ncludng a statc network smulator [5][6]. Table 1.1 and 1.2 ntroduce the smulaton parameters of ac and LTE A network. For ac, payload sze s assumed to be constantly 1500 bytes, and the A-MPDU of 5 MPDU s appled as frame aggregaton opton. The traffc model of W-F s fullbuffered for both DL and UL where the UL actvty factor β s 1/6. To model the practcal W-F nterference scenaro, we assume that one operator deployed W-F network receves external nterference from other three W-F networks owned by other moble operators and deployed close,.e. four W-F networks shared the unlcensed spectrum at 5 GHz band. Only SU-MIMO (sngle user MIMO) s modeled for ac. The ndoor W-F AP placement employs the traffc-drven algorthm descrbed n secton IV.C wth the mnmum nterste dstance (ISD) of 20 meters between APs, 20 meters to mcro ste and 50 meters to macro ste. We assume open subscrber group (OSG) for W-F access. For LTE-A traffc steerng, cell range extenson (RE) s appled to offload more users to mcro cell. Ths emulates the reference sgnal receved qualty (RSRQ) and cell range extenson procedure supported n LTE-A. Table 1.1: Smulaton Parameters of W-F ac Parameter W-F TX power W-F Payload Sze Frame Aggregaton W-F Traffc Model MIMO confguraton Carrer frequency Channelzaton Bandwdth W-F channel allocaton W-F Traffc Steerng Polcy W-F AP Placement Number of External W-F Networks Settng 20 dbm 1500 Bytes A-MPDU wth aggregaton of 5 MPDU subframes DL: full buffer, UL : full buffer wth actvty factor 1/6 2 x 2 SU-MIMO No support of MU-MIMO 5 GHz ( total 480 MHz spectrum) 40/80/160 MHz Unform Random SMART Indoor Traffc-drven deployment, mn ISD 20m to other APs, 20m to mcro cell, 50m to macro cell 3 external W-F networks are deployed Table 1.2: Smulaton Parameters of LTE Network and Deployment Scenaro Parameter Transmsson Scheme Macro Carrers (FDD) Mcro carrers (FDD or TDD) Transmt Power (Per Carrer) Antenna Confguraton Path Loss Model Traffc Model User Dstrbuton Traffc Steerng Polcy Settng Downlnk 2 x 2 MIMO (LTE-A) 10MHz@800MHz, 10MHz@900MHz 15MHz@1800MHz, 15MHz@2100MHz See Secton III.B Macro: 46 dbm. Mcro: 30 dbm, Macro: Real antenna pattern wth down-tlt angles; Mcro: 6 db real omn-antenna, antenna heght 5 m; Ray traced path loss for macro and mcro cells Modfed verson of [8] for WF Full Buffer 280 actve 10Mbps mn. data rate Measured user densty map (see Secton II) 30%-70% outdoor-to-ndoor user splt 50% of ndoor users located at the ground floor Mcro : Range Extenson wth RSRQ bas of 3 db A. W-F ac Offloadng & 3.5GHz Spectrum Allocaton Frstly, we study the feasblty of meetng 1000x network capacty demand by ndoor W-F ac deployment complementng the LTE-A network. Fg.2 shows the user outage per layer for varous W-F AP denstes from 0, 500, 1000, up to 1500 AP/km when the mnmum user data rate s 10 Mbt/s. Wthout any ndoor W-F deployment, the network suffers from user outage of 20% that s far above the 10% KPI requrement, even f outdoor mcro cell s deployed and 3.5GHz spectrum s allocated. Fg.3 shows the percentage of

6 ndoor and outdoor users n outage. The majorty of user outage comes from the macro served users that are located nsde the buldng area and also outsde the coverage of outdoor mcro cell. When 500 W-F AP/ km 2 are deployed n the ndoor area, a sgnfcant mprovement of user outage can be seen n fg.2, especally for ndoor user outage from macro cell. The user outage drops from 20% to 9%, whch s below the target maxmum 10% user outage. Note that, by SMART traffc steerng n secton IV, the W-F layer has always 0 user outage. The ncrease of AP densty from 500 to 1000 AP/ km 2 further mproves the user outage. However, as the number of APs ncrease from 1000 to 1500, the W-F offloadng gan saturates. To summarze, ndoor W-F densty of 500 AP/ km 2 (125 AP/macro ste) can help the LTE-A network meet the 1000x capacty demand when the mnmum user date rate s 10 Mbt/s provded that new 3.5GHz spectrum s allocated to mcro cell. Fg.4 shows the percentage of users served at each layer at the same set of confguratons n fg.2: ndoor W-F deployment offloads traffc both from macro and mcro cell: 500 AP/ km 2 offloads already more than 50% users; As the W- F densty ncreases from 1000 to 1500 AP/ km 2, the offloadng gan gradually saturates,.e. from 65% to 69% users offloaded to W-F, because ndoor W-F already offloads almost the upper lmt of all ndoor users that account for 70% of all users. Indoor W-F serves mostly only ndoor users, but not outdoor users because the deep wall penetratons and low transmsson power prevent W-F s outdoor coverage. s 1500/ km 2 and the mnmum user data rate s 10 Mbt/s, our smulaton results show that the network acheves user outage of 4.8% whch s far below the target maxmum 10% user outage KPI. Due to the lmted space of the paper, we do not ntend to show the detaled results of ths case. Fg. 4. User Dstrbuton vs. W-F densty/ km 2 Fg. 2. User Outage vs. W-F Densty/ km 2 Fg. 3. Indoor/Outdoor Outage vs. W-F Densty/ km 2 Secondly, on condton that new 3.5GHz spectrum s not avalable, can ndoor W-F deployment stll meet the 1000x capacty demand? Assumng that the deployed W-F densty Fg. 5. W-F ac Traffc Steerng B. Impact of W-F Traffc Steerng Polcy We compare two traffc steerng polces - SMART and Best-Server as n secton IV.A. Assume the same network confguraton as above: user mnmum data rate requrement s 10Mbt/s, W-F densty s 500/km 2. Fg.5 shows the performance superorty of SMART n terms of user outage: wth SMART, there s no user outage at W-F layer snce there s a data-rate based user admsson control,.e. only users that can acheve the mnmum data rate are admtted to W-F; however, wth Best-Server, there s 4% user outage at W-F layer. The macro/mcro layer performance s dentcal for the two traffc steerng polces. C. W-F Channel Bandwdth Optons at 5GHz We also study varous channel bandwdth optons of ac at 5GHz band. Due to lack of space, the results are not shown here. Wth ac, the channel bandwdth can be bonded to 40/80/160 MHz, whereas the number of orthogonal channels are 12/6/3 respectvely. As stated n secton IV.B, the unform channel assgnment s assumed. Interestngly, our results show that the network performance s not so senstve to the bandwdth confguraton: a bandwdth of 40 MHz gves only a slghtly better performance than a bandwdth of 80 or 160 MHz. Even f a very large bandwdth can brng more capacty at one W-F cell, t sacrfces the overall spatal

7 frequency reuse gan,.e. less orthogonal channels can be allocated to neghborng cells, whch lead to hgher nter-cell nterference, and fewer users can be offloaded to W-F due to the mnmum SINR threshold. D. Dscusson on the Mult-Floor AP Deployment We manly study the W-F deployed on the ground-floor, snce 50% UEs are assumed located n ground floor whle UEs at hgher-floor are already served by outdoor mcro and macro cells. We are under an on-gong study on the mult-floor deployment n scenaros where the traffc dstrbuton s unform vertcal among floors and especally n scenaros where there are many hgh-rse buldngs (e.g. 100 m above) wth lmted outdoor mcro / macro coverage. VI. CONCLUSION We quanttatvely study the ndoor W-F ac deployment as the capacty expanson soluton of LTE- Advanced to meet 1000x capacty/traffc wth a target user data rate of 10Mbt/s or hgher. For the performance modelng, we propose a novel analytcal throughput model that captures both key ac features and W-F mult-cell nterference. The model s well valdated by detaled system-level smulatons. We conclude that W-F at 5Ghz wll play an mportant role for the 1000x moble network capacty demand. Deployment of outdoor mcro cells certanly boost network capacty, but we stll see hgh outage n provdng the target user data rate of 10Mbt/s or hgher. Deployng ndoor W-F access pont at 5GHz n each buldng offload up to 70% of the traffc from the cellular network, and mprove sgnfcantly the ndoor coverage and ensure very low outage n delverng a mnmum user data rate of 10Mbt/s. REFERENCES [1] QUALCOMM whte paper, Rsng To Meet 1000x Moble Data Challenge, June [2] Mogensen P., et al., B4G Local Area: Hgh Level Requrements And System Desgn, to appear n Proc. Globecom, December [3] H.Ish et al, A Novel Archtecture for LTE-B: C-plance/U-plance Splt and Phantom Cell Concept, IEEE Proc. Globecom, December [4] Csco techncal whte paper, ac: The Ffth Generaton of W- F, Csco Publc Informaton, August 2012 [5] L.Hu et al, Realstc Indoor W-F and Femto cell deployment as the Offloadng Solutons to LTE Macro Network, IEEE Proc. VTC, September 2012 [6] C.Colett et al, Heterogeneous Deployment to Meet Traffc Demand n a Realstc LTE Urban Scenaro, IEEE Proc. VTC, September 2012 [7] Kovacs, I.Z.; Mogensen, P.; Chrstensen, B.; Jarvela, R.: Moble Broadband Traffc Forecast Modelng for Network Evoluton Studes, IEEE Proc. VTC, September 2011 [8] A.Duda et al, Understandng the Performance of Networks, IEEE Proc.PIMRC, September 2008 [9] ITU-R, Estmated Spectrum Bandwdth Requrements For The Future Development of IMT-2000 and IMT-Advanced, M