Transactions on Emerging Telecommunications Technologies. Scalability Study of Backhaul Capacity Sensitive Network Selection Scheme in LTE-WiFi HetNet

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1 Page of Transactons on Emergng Telecommuncatons Technologes Scalablty Study of Backhaul Capacty Senstve Network Selecton Scheme n LTE-WF HetNet Alvn Tng, Davd Cheng, Kae Hsang Kwong Wreless Communcaton, MIMOS Berhad, K.L, Malaysa. {kee.tng, ht.cheng, kh.kwong}@mmos.my Abstract Wreless Heterogeneous Network (HetNet) wth small cells presents a new backhaulng challenge whch dffers from those of experenced by conventonal macro-cells. In practce, the choce of backhaul technology for these small cells whether fber, xdsl, pont to-pont and pont-to-multpont wreless, or mult-hop/mesh networks, s often governed by avalablty and cost, and not by requred capacty. Therefore, the resultng backhaul capacty of the small cells n HetNet s lkely to be non-unform due to the mxture of backhaul technologes adopted. In such an envronment, a queston then arses whether a network selecton strategy that consders the small cells backhaul capacty wll mprove the end users usage experence. In ths paper, a novel Dynamc Backhaul Capacty Senstve (DyBaCS) network selecton schemes (NSS) s proposed and compared wth two commonly used network NSSs, namely WF Frst (WF) and Physcal Data Rate (PDR) n an LTE-WF HetNet envronment. The proposed scheme s evaluated n terms of average connecton or user throughput and farness among users. The effects of varyng WF backhaul capacty (unform and non-unform dstrbuton), WF-LTE coverage rato, user densty and WF access ponts (APs) densty wthn the HetNet form the focus of ths paper. Results show that the DyBaCS scheme generally provdes superor farness and user throughput performance across the range of backhaul capacty consdered. Besdes, DyBaCS s able to scale much better than WF and PDR across dfferent user and WF denstes. Ivan Andonovc CIDCOM, Dept. EEE, Unversty of Strathclyde, Scotland, UK.andonovc@eee.strath.ac.uk For Peer Revew Keywords - Hetrogeneous Network, Network Selecton, LTE, WF, Traffc Offload, Backhaul Capacty. Introducton The ncreasng pressure for moble operators to offload data traffc from ther G, LTE or WMAX networks to small cell networks [] [] ndcates that future moble broadband networks wll largely be heterogeneous. Ths mgraton s further fueled by the avalablty of mult-rat (Rado Access Technology) whch allows user devces to connect to dfferent wreless networks such as G, LTE, WMAX, WF ether one at a tme or smultaneously. Deployment of small cells such as WF rases new backhaul challenges for operators. There are only two broad choces as far as backhaul s concerned, Capacty and throughput are used nterchangeably throughout artcle wth the detal defnton n secton. K. D. Wong Danel Wreless LLC Palo Alto, CA, USA dwong@danelwreless.com wrelne and wreless backhaul. Due to ntensve engneerng work requred, hgh cost and regulatory barrers, fxed lne solutons such as fber, cable, copper or xdsl are not ubqutously avalable. Further, a relatvely large number of WF hotspots may prove too costly for operators to backhaul wth wred optons. In such stuatons, the operator may nstead ncreasngly rely on pont-to-pont and pont-to-multpont wreless solutons. However n most scenaros, a mxture of backhaul technologes s expected, as operators wll adopt the most sutable backhaul soluton for small cells consderng the cost and avalablty [] (Fgure ). Wth the maturty of multhop mesh networks, t may also serve as a potental canddate [] []. Currently, WF APs are typcally backhauled through dfferent types of technologes whch offer throughput capacty rangng from several mega bt per second (Mbps) to tens of Mbps []. Backhaulng APs usng dfferent technologes wthn the HetNet leads to non-unform AP capacty dstrbuton. The most wdely deployed IEEE0.n WF technology whch provsons a peak physcal data rate of 00Mbps. Due to that most exstng fxed backhaul servces are not able to offer suffcent capacty for these WF APs to realze ther full potental. Therefore consderaton of WF backhaul capacty s nevtable durng traffc offload decson makng. wred Backhaul WF Fgure : LTE-WF Heterogeneous Network wth dfferent backhaul optons... Related Work WF WF wred backhaul Wreless Backhaul To reduce data traffc pressure over moble networks, alternatve networks such as WF are preferred by moble operators whenever possble []. As report n [], most WF-enabled smartphones are confgured wth WF Frst network selecton scheme by default to gve WF hgher prorty over the cellular nterface for data transmssons. Network selecton strateges for WMAX-WF network whch LTE WF WF

2 Transactons on Emergng Telecommuncatons Technologes Page of s predomnantly drven by data rate are reported n [] and []. Ths knd of network selecton strateges lead to poor user experences [0] and causes unbalanced load dstrbuton amongst access networks []. Several studes [-] have proposed the use of Network Selecton Schemes (NSSs) to optmze network performance. The work by [] consders a globally optmal user-network assocaton scheme n a WLAN-UMTS hybrd cell. In [], a heurstc greedy search algorthm that maxmzes total user throughput n a heterogeneous wreless access network comprsng WF APs and G BSs s proposed. Both these studes adopt a smplfed WLAN model by assumng only one transmsson rate. Posson pont process (PPP) theory and stochastc geometry method are used n [] to model traffc offloadng n a mult RAT heterogeneous wreless network. The authors propose a method to determne the optmum percentage of the traffc that needs be offloaded n order to maxmze network coverage whle meetng user requrements. In that work however, no network selecton algorthm s proposed. For Peer Revew Farness performance s consdered n [-] where [] focuses on ensurng max-mn farness for multcast n Orthogonal Frequency Dvson Multple Access (OFDMA)- based wreless heterogeneous networks. A proportonal user rate based rado resource management strategy s nvestgated n [] on LTE-WF HetNet, where a suboptmal network selecton algorthm s ntroduced to mprove the mnmum normalzed user rate and farness. Bejerano et al. [] proposes changes to the transmsson power of AP beacon messages n order to mnmze the load n congested APs and produces an optmal max-mn load balancng strategy. A load balancng scheme for overlappng wreless LAN cells s reported n []. However, the work ams to balance the throughput of APs and not the farness amongst users. NSSs that consder QoS are reported n [] [] []. Network selecton based on multple parameters such as cost, bandwdth and QoS parameters ncludng packet loss, jtter and delay s reported n []. However, the study focuses only on general heterogeneous networkng and no specfc type of technology s smulated. Smlarly, the work n [] and [] nvestgate access network selecton for optmal servce delvery and QoS to users respectvely. However the overall HetNet performance and farness s not consdered. Load balancng n Cellular and WLAN HetNet s reported n [] [0] and []. In [], a jont access-control strategy s desgned for sharng of the rado resource and load balancng between CDMA Cellular Network and WLANs by consderng user preferences. Bandwdth allocaton s optmzed by maxmzng the aggregated socal welfare of the WLANs under nterference-constrant envronment. However, the method used to balance the load amongst moble nodes s not dsclosed. The work n [0] looks nto the trade-off between the amount of traffc beng offloaded and users satsfacton. An ncentve framework s proposed to motvate users to use delay tolerance WF networks for traffc offloadng. Yang et al. n [] proposes a load balancng scheme that ams to balance the network load between the LTE network and WF hotspots consderng access pattern of UEs. Bejerano et al. [0] consders backhaul capacty durng AP selecton, whle [] proposes a backhaul-aware base staton (BS) selecton algorthm. Although backhaul-aware network selecton scheme have been explored n these works, ther scope s lmted to homogeneous wreless networks. In ths paper, a Dynamc Backhaul Capacty Senstve (DyBaCS) NSS s proposed for LTE-WF HetNet. Ths scheme not only consders access lnk throughput but also avalable backhaul capacty n order to preserve farness amongst users. The proposed scheme s compared wth two commonly used NSSs namely WF Frst (WF) and Physcal Data Rate (PDR). Ths paper nvestgates farness and average user throughput performances across WF backhaul capacty rangng from Mbps to Mbps. The rest of the paper s organzed as follows. Secton descrbes the proposed DyBaCS network selecton algorthm as well as WF and PDR schemes. Secton detals the smulaton approach, smulaton parameters and assumptons made. Results are dscussed n Secton followed by conclusons n Secton.. Exstng and Proposed Network Selecton Schemes Ths secton descrbes the smulaton approach smulaton parameters and assumptons used n the study. The notatons used are lsted n TABLE I. Notaton N cluster σ x, σ y N user SINR SNR p u p I NF C Av R φ T PL d NLOS OF EIRP WF DyBaCS PDR MAC UE TABLE I : NOTATIONS Descrpton number of clusters for user dstrbuton wdth and heght of user dstrbuton clusters number of users n a cluster sgnal to nterference and nose rato sgnal to nose rato WF receve power by user u WF nterference power nose floor average user throughput WF downlnk physcal transmsson rate to users lnk throughput effcency measured at the IP layer maxmum downlnk throughput achevable by a LTE user path loss n db dstance n meters Non-lne-of-sght overbookng factor effectve sotropc radated power WF Frst network selecton scheme Dynamc Backhaul Capacty Senstve network selecton scheme Physcal Data Rate Based network selecton scheme medum access control user equpment C sys system throughput of AP LTE C sys N user LTE N user HetNet N user C lnk,u LTE system throughput wthn the HetNet total number of users n AP total number of users n a LTE cell total number of users n HetNet access lnk throughput from AP to user u

3 Page of Transactons on Emergng Telecommuncatons Technologes LTE C lnk,u access lnk throughput from LTE BS to user u C bh backhaul capacty of AP n Mbps C Av,ltd average AP users throughput wth lmted backhaul capacty C Av average AP users throughput wth suffcent backhaul capacty effectve user throughput C eff C n C n LTE Ω A.. Network Capacty Model estmated throughput f user n s connected to AP estmated throughput f user n s connected to LTE BS lst of hgher speed connectons (amongst WF and LTE nterfaces for a user) for all users n throughput set that contans all users n the HetNet... Sngle WF AP wth Max-mn Farness In a mult-rate WF network, users wth slower lnk speed tend to occupy more spectrum resource (n terms of transmt tme) than hgher speed users for the same amount of data sent. Such a bandwdth sharng scenaro amongst all users wthn a sngle AP coverage has been modelled. For Peer Revew Suppose a total of N user users are connected to an AP and each s supported by a data rate, R u n accordance to ther SINR level. Thus, user u receves transmsson slots at rate R u bps, where u =,.. N user. Assumng the channel access probablty s P u and t exhbts the effect of slots assgnment, whch s nversely proportonal to user data rate R u. Let S u be the number of slots allocated to user u, where S u = k/r u, wth k beng an arbtrary constant whch wll be cancelled off eventually. In ths case, f user packet sze s assumed to be the same, the AP throughput at the physcal layer can be calculated as [] []: C Phy sys = Nuser u= P ur u S u Nuser u= P u S u Substtutng S u = k R u nto Eqn (); C Phy sys = Nuser P ur u ( k u= Ru ) = k Nuser Nuser P u ( k u= P u = Nuser u= Ru ) k Nuser P u= P u u u= Nuser P u R u u= R u N user Snce the sum of P u by all user s u= P u =, Eqn () can be further smplfed to: C Phy sys = Nuser P u u= R u The average physcal layer throughput per user C Phy Av s calculated by dvdng Eqn () wth the total number of users N user Snce far resource sharng s assumed, whch n turn mples that the packet sendng frequency of every user s the same, the P u of a user can also be wrtten as : N user () () () C Phy Av = ( ) ( N user Nuser u= Nuser Ru ) = Nuser u= Ru The model facltates max-mn farness [] [] behavor n a mult-rate system where all users are allocated an equal amount bandwdth resource. Ths characterstc s representatve of WLAN Dstrbuted Coordnated Functon (DCF) [] where all users are offered a far medum access opportunty. Example : Assume two users are connected to an AP wth supported data rate of R = Mbps and R = Mbps respectvely. The number of tme slots assgned s nversely proportonal to data rate hence S = k = k and S R = k = k, where k s R an arbtrary constant. The channel access probablty of user and user are represented by P and P. Snce both have a far chance to transmt to the AP or vce versa, P = P =. Wth both users takng turn to transmt packets and f ther packet szes are the same, the tme taken by each user to transmt a packet can be represented by Fgure. User User ( R = Mbps) ( R = Mbps) () Fgure : Tme slots requred by user and user consderng far throughput From Fgure, User takes more tme than User n order to mantan throughput farness. In other words, User s beng penalzed n terms of tme slot farness, whch s the characterstc of WF DCF system. The average throughput for both users can be calculated usng Eqn () as follows: C Phy AV = 0. S = k 0.0 S = k S S +S R = S S +S R () By substtutng the values of S, S, R and R nto Eqn (), the average throughput for both users can be calculated as. Mbps. Smlarly, wthn a sngle WF network, the average IP layer throughput per user C Av (Eqn ()) s calculated by multplyng the physcal data rate R u n Eqn () by a correspondng throughput effcency factor φ u gven n TABLE V: C Av = Nuser u= Ru φu The accuracy of the model (mplementaton of Eqn ()) s verfed together wth the IEEE0.g WF models (n ()

4 Transactons on Emergng Telecommuncatons Technologes Page of secton.) usng the QualNet event-drven smulator (Verson.) and the results are found to be very smlar.... LTE wth Max-Mn Farness In LTE, resource s assgned to users n forms of Physcal Resource Blocks (PRB) consstng of many Resource Elements. The same max-mn far bandwdth sharng approach s adopted where n the LTE case, more PRBs are assgned to users experencng worse channel behavor to ensure farness. Ths assumpton s reasonable snce the LTE Medum Access Control (MAC) scheduler has not been fully defned n the standards. In order to smplfy the study, resource element allocatons n LTE are approxmated as tme fracton allocaton n a TDMA manner as modeled n [] and the average user throughput s defned by Eqn (), a straghtforward modfcaton from Eqn (): C Av = NLTE user u= Tu () For Peer Revew where T u s maxmum lnk throughput achevable by LTE user u and N LTE user s the total number of LTE users... Network Selecton Schemes In a heterogeneous wreless network comprsng two or more technologes, user throughput farness needs to be consdered n two aspects, ntra-network farness and nternetwork farness. Intra-network farness can be provded by AP or LTE BS to ts assocated users as the task s confned locally. Wth max-mn far capacty sharng of WF and LTE network (Eqn () and Eqn ()), farness s achevable amongst users under the same AP or BS. However, far capacty sharng across the entre HetNet s not guaranteed and s strongly dependent on the mplemented NSSs. The proposed DyBaCS s compared wth two commonly used NSSs namely WF Frst (WF) and Physcal Data Rate (PDR), the characterstcs of whch are as follows:... WF Frst (WF) WF Frst (WF) connects a user to an AP whenever WF coverage s avalable. In other words, a user wll never connect to a LTE network when there s WF coverage. Ths approach s adopted by most smart phones and tablets connecton manager by default as the preferred data connecton mode. In addton, ths mode s also promoted by some moble operators as a means to offload traffc from moble networks [0] [].... Physcal Data Rate (PDR) PDR chooses the network based on the Physcal data rate of the RAT avalable to the user [] []. Here the physcal data rates provded by LTE and WF are compared and the RAT wth hgher physcal data rate s chosen. Snce PDR tends to assgn more bandwdth to the users wth better lnk capacty, t compromses user farness, though the overall throughput performance mght be good.... Proposed Dynamc Backhaul Capacty Senstve (DyBaCS) scheme DyBaCS s manly proposed to preserve farness whle maxmzng HetNet throughput. Thus DyBaCS throughput performance may not outperform PDR (whch s optmum n mantanng HetNet throughput), but t s very close to PDR n most cases (Secton ). In the study, a sngle LTE network s assumed wth I (I ) denotng the total number of WF APs n the HetNet and denotng the ndex of the network,.e. network = I s the -th WF network, whle, HetNet u = u N user represents the u-th user n the HetNet and U s the total user n entre HetNet. Total number of users n AP and LTE network s represented by U and U LTE respectvely. Before explanng the DyBaCS algorthm n detal, Algorthm ; the User Throughput Estmaton Flow (UTEF) algorthm, whch enables the estmaton of WF user LTE throughputs C eff,u and LTE user throughputs C eff,u s frst presented as follows: Algorthm : Users Throughput (C eff,u ) Estmaton Flow (UTEF) a) WF UTEF: ) Let u = {,,,N user } } s number of WF users n Network ) Average user throughput s : C Av = ; Eqn () N user u= R u φu ) System throughput for network s: C sys ) For u = to N user A) If C bh C sys ) C eff,u = { C Av OF C Av Otherwse C lnk,u = C Av N user OF C lnk,u B) Elsef C bh < C sys ) C Av,ltd = C bh /N user ) f C Av,ltd OF C lnk,u a) C eff,u = { C Av,ltd OF C Av,ltd OF < C bh otherwse ) If C Av,ltd a) C eff,u C bh OF > C lnk,u = { C lnk,u C lnk,u < C bh Otherwse C bh b) LTE UTEF: ) Let u = {,,,N LTE user } s number of users n LTE Network ) Average user throughput s : C LTE Av = LTE ; Eqn () N user u= ) Average user throughput consderng OF s: C LTE eff,u Tu LTE = { C Av OF C Av OF C lnk,u LTE LTE C lnk,u C Av OF < C lnk,u For WF UTEF (Algorthm ), the calculaton of effectve WF user throughput C eff,u s based on user access lnk throughput C lnk,u, AP backhaul capacty C bh and Overbookng Factor (OF). Lnk throughput C lnk,u (or equvalent to R u φ u n Eqn () and φ u s lsted n TABLE V) of user u s predomnately affected by the dstance from the AP, channel qualty and other channel condtons such as nterference. Backhaul capacty C bh s defned as the actual avalable backhaul capacty to AP, whether t s wred or wreless backhaul. Effectve user throughput s lmted by both

5 Page of Transactons on Emergng Telecommuncatons Technologes factors. In practce, OF s normally consdered as not all the users access the channel at the same tme []; by ncludng OF the perceved throughput from the users pont of vew can be calculated. The calculaton of effectve user throughput n WF UETF can be explaned n detal wth the ad of the scenaro shown n Fgure, where users are connected to AP. User data rate R u and lnk throughput C lnk,u are lsted n TABLE II. Fgure : AP wth users under ts coverage TABLE II : USER DATA RATE AND LINK THROUGHPUT IN Fgure User, u R u C lnk,u = R u φ u 0. =. 0. =. 0. =. 0. =. For Peer Revew Step and Step n Algorthm estmate the average WF user throughput usng Eqn () and the average user throughput can be calculated as: C Av = u Access Pont R = N user u= Core Network R = u = R u φ u R + φ R + φ R + φ R φ = =. M () Multplyng the average user throughput C Av by the total number of users N user, as n Step, yelds the total system throughput C sys of AP: C sys WF user AP s Backhaul BW, C bh = 0 / = C Av AP R = N user () In the scenaro, C sys =. =. Mbps. As n Eqn (), C sys s affected by lnk speed R u of all users n network ; therefore t s hghly dependent on users dstrbuton. C sys represents the requred backhaul capacty for AP to realse ts full access capacty. If the backhaul capacty s suffcent to support the maxmum capacty from the AP to clents such u WF Lnk R = u AP s Backhaul that C bh C sys, then all users wll enjoy a throughput of C Av. However, f the backhaul capacty C bh s the bottleneck, C bh C sys, the avalable backhaul capacty C bh s shared evenly to all users N user and average user throughput n such scenaro s lmted to a value C Av,ltd (Eqn (0)) whch s less than C Av. C Av,ltd = C bh /N user (0) It s mportant to note that users wll not secure a throughput hgher than C Av even at backhaul capactes greater than C sys due to the restrcton mposed by the WF physcal and MAC layer capablty. Under the assumpton of smultaneous channel access, C Av or C Av,ltd represents the average user throughput for both suffcent and lmted backhaul capacty cases. In Fgure, assumng that backhaul capacty C bh = 0 s less than C sys =., the actual average throughput for the users s lmted to C Av,ltd = Otherwse, each user wll enjoy C Av C sys. C bh N = 0 user =. Mbps. =. Mbps f C bh In order to smplfy the explanaton of Algorthm, an OF = s adopted for scenaro depcted n Fgure. Suppose C bh = Mbps where C bh C sys, the effectve average throughput C eff,u of user u s only lmted by ts lnk throughput C lnk,u. Step A () places a constrant to ensure that the value of C Av OF does not exceed C lnk,u. TABLE III shows that effectve user throughput C eff,u s the mnmum value between C Av OF and C lnk,u. Note that the effectve average throughput for User and User s lmted to ther lnk throughput whch s. Mbps and. Mbps respectvely. User, u TABLE III : EFFECTIVE USER THEROUGHPUT C eff,u UNDER CONDITION C bh C sys. C Av C bh C lnk,u C Av OF C eff,u Lkewse, wth lmted backhaul capacty, Step B () and Step B () ensure that C Av,ltd OF s bound by both C lnk,u and C bh, whchever s smaller. The result s shown n TABLE IV. TABLE IV : EFFECTIVE USER THROUGHPUT C eff,u UNDER CONDITION C bh C sys. User, u C Av C bh C lnk,u C Av OF C eff,u

6 Transactons on Emergng Telecommuncatons Technologes Page of In short, Step mposes logcal consderatons to the determnaton of the effectve user average throughput C eff,u takng nto consderaton backhaul capacty, user lnk speed and OF. Smlarly, the LTE user throughput can also be estmated usng the LTE UTEF approach. In ths paper, LTE backhaul capacty s always assumed to be suffcent. Therefore n Step, the only constrant for user throughput n the LTE network s the access lnk throughput C LTE lnk,u. The DyBaCS NSS (Algorthm ) assumes that ntally, there s no user connected to the HetNet. Users are admtted to the HetNet one by one and ther servcng network s determned by the NSS. Step ntalzes varables Ω, A,N user and N LTE user, where Ω s a lst holdng the hgher speed connectons between WF and LTE nterfaces to users, A s the set contanng all users n the HetNet, N user s the lst of users connected to the WF AP LTE and N user s the lst of users connected to the LTE network. For Peer Revew In Step, the access lnk wth the hghest throughput between user u to LTE (C LTE lnk,u ) or WF (C lnk,u ) s chosen and placed nto Ω, Ω u represents the throughput value for user u. All users are able to connect to at least the LTE network whle access to WF depends on avalablty of WF coverage. Hence β u = {0,} denotes the connectvty of user u to AP, β u = means connecton s possble, 0 means the opposte. Snce mult-homng s not consdered, every user s only allowed to connect to one network at a tme. Step assgns all users wth no WF access to the LTE network and excludes those users from set A. The network selecton parameter α u {0,} ndcates the choce of user u; α u = ndcates that user u s connected to network and value 0 means the opposte. The remanng users wthn set A whch have not been assgned to any network are subjected to network selecton; they can ether assgned to WF or LTE. Network selecton for those users s addressed n Step n order to optmze the network performance. Step (a) ensures the user wth the hghest lnk throughput wthn set A (referred to as user n) s consdered frst. In Step (b) and Step (c), the achevable throughput of user n (consderng access lnk speed, AP backhaul capacty and OF) on WF AP and LTE s estmated usng WF LTE UTEF and LTE UTEF and represented by C eff,n and C eff,n respectvely. The throughput estmaton s executed assumng that user n s added to the correspondng WF or LTE network. Therefore, durng the throughput estmaton, the total number of users connected to AP s assumed to be user n plus the total number of exstng users N user wrtten as N user {n} and smlarly the total number of users n the LTE network s N LTE user {n}. The achevable throughput for user n on the WF and LTE network s then assgned to C n LTE and C n respectvely. User n s subsequently assgned to the network that offers the hghest throughput and the correspondng α n LTE or α n value s set accordng to Step (d). The total number of users connected to ther respectve -th WF network N user or LTE LTE network N user s then updated. Fnally set A s updated by excludng user n n Step (e) and the Step processes are repeated untl all users are servced. Algorthm : DyBaCS ) Intalzaton a) Ω =, and A = {,,, N HetNet user } b) U =, = {0,, I}; N LTE user = HetNet ) For u = to N user a) Ω u max(β LTE u C lnk,u, C lnk,u ), = {0,, I} HetNet ) For u = to N user a) f user u satsfyng β u = 0, = {,, I}. α LTE u =. A = A {u} ) whle A a) fnd n where Ω n Ω u for all u A and b) Estmate user n throughput C eff,n n -th WF Network assumng user n s ncluded to the network,.e. N user {n}; Usng WF UTEF (Algorthm a). C WF n C eff,n LTE c) Estmate user n throughput C eff,n n LTE Network assumng user n s ncluded to LTE Network,.e. N LTE user {n}; Usng LTE UTEF (Algorthm b);. C LTE LTE n C eff,n d) If C LTE n C n. α LTE n = LTE. N user = N LTE user {n} Else. α n = v. N user = N user {n} e) A = A {n}. Parameters, Assumptons and Smulaton Approach The secton descrbes the smulaton approach, smulaton parameters and assumptons used... WF Model TABLE V presents the parameters used n the WF IEEE0.g model. The recever senstvty values per modulaton and codng scheme (MCS) for WF recevers are taken from []. The throughput effcency, the rato of actual IP layer throughput aganst physcal data rate and the actual IP layer throughput of each MCS scheme are obtaned from the QualNet smulator assumng fxed packet sze of 000 Bytes wth constant bt rate traffc. Index MCS TABLE V : IEEE0.G PARAMETERS Recever Data Throughput Senstvty Rate Effcency (dbm) (Mbps) (φ) Throughput (Mbps) BPSK/ BPSK/ QPSK/ QPSK/ QAM/ QAM/ QAM/ QAM/

7 Throughput (bts/sec/hz) Page of Transactons on Emergng Telecommuncatons Technologes The path loss model n Eqn () s derved from feld measurement detaled n [] :.. LTE Model PL = 0. log0(d) +. () LTE throughput s calculated based on the throughput plot by GPP [] shown n Fgure. In the smulaton, SINR rato at a recever s used to calculate the achevable throughput. In order to calculate the receved power, the ITU recommended LTE Urban Macro (UMa) non-lne-of-sght (NLOS) path loss model s used []. QPSK / QPSK / QPSK / QPSK / QPSK / QPSK / QPSK / QAM / QAM / QAM / Fgure : LTE throughput vs. SNR for dfferent Modulaton and Codng Schemes (MCS) used n the model.. Stochastc User Placement Model QAM / QAM / QAM / For Peer Revew SNR (db) A stochastc node locaton model s used to poston the users n the HetNet. The authors n [] found that ths model can represent the users locatons around WF AP n a cty or urban envronment. Here users are assumed to be dstrbuted around cluster centers. Two spatal dstrbutons model are adopted where the frst dstrbuton s used to generate the numbers and locatons of the cluster centers. The second dstrbuton s then used for postonng the number of users around each center. The ntal cluster center dstrbuton s generated randomly wth total number of cluster centers equal to N cluster. Subsequently, a bvarate Gaussan dstrbuton wth covarance matrx = dag(σ x, σ y ) s used to generate actual user locatons around the cluster centres. The sze and shape of the cluster s characterzed by the parameters σ x and σ y (Fgure ). The number of users per cluster s drawn from a Posson dstrbuton wth ntensty N user. Parameters σ x, σ y and N user are the same for every cluster. In the smulaton, ntally 00 users are placed n an area of square klometre wth number of clusters N cluster = 0, cluster sze N user = 0 and σ x = σ y =. Subsequently 0 users are added each tme by ncreasng number of cluster N cluster by fve whle keepng the number of users per cluster N user and cluster dmenson σ unchanged, untl the total number of users reaches 0 (Fgure ). Snce all users are tabulated n an area of square klometre, the terms the number of users and user densty are used nterchangeably n the rest of ths paper. Fgure : User placement wth total number of clusters N cluster = 0, cluster sze N user = 0 and σ = Fgure : User placement from 00 users to 0 users wth 0 users added every tme, maxmum N cluster =, cluster sze N user = 0 and σ =.. Placement of WF Access Ponts Fgure : WF APs placement wthn HetNet that comprses the scenaros wth, and WF APs In the Matlab model, WF APs are placed wthn a macro LTE cell accordng to three selected topologes shown n Fgure. These WF topologes enable the NSSs to be evaluated as a functon of WF-LTE node ratos (or WF node denstes). By controllng the APs transmt power, these WF topologes can gve the same coverage sze as the macro LTE cell. For example, Fgure a shows the coverage plot for APs, whle the overlay of both WF and LTE cell (Fgure b) that forms the HetNet s llustrated n Fgure c. WF coverage plots for and APs are shown n Fgure a and Fgure b respectvely. Although there s no lmt on the varaton topologes whch can be evaluated, the selected topologes s beleved to be able to provde a good nsght on the performance of NSSs under dfferent WF-LTE node ratos.

8 Transactons on Emergng Telecommuncatons Technologes Page of (a) (c) (b) For Peer Revew Fgure : Network coverage plot based on data rate wth x and y axs showng coverage sze n meter; a) -WF-Nodes networks wth access channel shown n parentheses, b) LTE network and c) HetNet (LTE+WF) wth 00 users (a) Fgure : WF coverage plot based on data rate wth x and y axs showng coverage sze n meter; a) -WF-Nodes networks, b) -WF-Nodes networks; WF access channel shown n parentheses.. WF Access Channel and Interference On WF access channel, three non-overlappng channels wth channel number, and are used (channel number s stated on top of each AP n Fgure and Fgure ). To calculate SINR, the smulated area s dvded nto -by- square meter grds. Snce non-overlappng channels are used, only cochannel nterference s consdered. In each grd, an effectve SINR s derved as: SINR = (b) p u M () t= p I +NF where, p u s the receved power of user u from the servng AP located n a grd, M s total number of co-channel nterferer APs n range, p I s the nterference power at the recever and NF u s the nose floor. Effectve SINR obtaned s then used to map user data rate and hence user throughput calculaton n WF networks AP() AP() AP() Fgure 0: -WF-Nodes coverage plot wth co-channel nterference Fgure 0 shows the coverage plot of WF nodes wth cochannel nterference. The nterference has resulted n a smaller effectve WF coverage area as compared to Fgure a, whch has a better channel plan... WF and LTE backhaul AP() AP() AP() In the study, WF backhaul capacty s vared from Mbps up to Mbps untl the throughput of AP saturates (Secton ). Two backhaul scenaros are assumed when evaluatng the NSSs; ) unform WF backhaul capacty and ) non-unform WF backhaul capacty throughout the HetNet. The LTE base staton (BS) backhaul capacty s always assumed to be suffcent... General Parameters and Assumptons AP() TABLE VI summarzes the smulaton parameters used. Only the downlnk performance s nvestgated n the paper..ghz s used for LTE as t s the frequency band allocated n Malaysa. A fxed nterference margn of db s assumed for the LTE User Equpment (UE). TABLE VI : WIFI AND LTE SIMULATION PARAMETERS Unts WF g LTE Frequency band GHz.. Channel bandwdth MHz 0 0 Max EIRP dbm,, Rx antenna gan db 0 Antenna dversty gan db Nose Fgure db Not requred 0 Packet sze Bytes 000 WF backhaul capacty Mbps LTE backhaul capacty Mbps Suffcent capacty assumed User Informaton Overbookng Factor, OF - 0: User densty Users/sqkm 00, 0, 00, 0 Recever antenna gan of WF and LTE UE s assumed to be db and 0 db respectvely. The assumpton on traffc type has been descrbed n Secton... From [], the Overbookng Factor (OF) s a desgn choce drven by actual user behavor n the deployed area. OF that vares from : to 00: has been reported by varous ISPs and the lower the

9 Page of Transactons on Emergng Telecommuncatons Technologes Fgure : HetNet average user throughput as a functon of WF backhaul capacty. ( WF APs, 00% WF-LTE overlap, Unform WF backhaul capacty) For Peer Revew value the better the servce guarantee. A factor of 0: n adopted to represent a relatvely heavy usage scenaro. User densty s vared from 00 users to 0 users per square km.. Results and Analyss.. Effect of Varyng Backhaul Capacty Unformly Two performance metrcs namely average user throughput and user throughput farness n the HetNet cell are used to evaluate the performance of the NSSs. Farness s derved N usng Jan farness ndex n the form of ( user u= C eff,u ) / N (N user (C eff,u ) user u= ) []. Frst the performance of all NSSs s evaluated as a functon of WF backhaul capacty from Mbps to Mbps wth 00% WF-LTE coverage overlap and WF APs (as n Fgure c). Fgure shows that average user throughput of PDR and DyBaCS are smlar over the entre range of backhaul capacty and WF has the lowest average user throughput. The plots plateaus when backhaul capacty reaches 0Mbps for all NSSs as that s the maxmum access throughput achevable by WF (IEEE 0.g). The total WF access throughput also depends on user dstrbuton as slower users slow down the entre network. Fgure evaluates the farness n terms of achevable throughput per user. Result shows that average user throughput of PDR and DyBaCS are smlar over the entre range of backhaul capacty whle WF has the lowest average user throughput. DyBaCS outperforms the rest n terms of farness and WF exhbts the worst farness performance. Fgure : Farness on bandwdth sharng as a functon of WF backhaul capacty. ( WF APs, 00% WF-LTE overlap, Unform WF backhaul capacty).. Effect of WF-LTE Overlap Rato Wthn a HetNet cell Snce the coverage overlap between WF and LTE s lkely to vary n practce, t s therefore mportant to nvestgate how NSSs perform n dfferent overlap condtons. Here the coverage area s defned as a percentage e.g. % means % of LTE coverage s also covered by WF and 00% means all LTE coverage s overlapped by WF. The smulaton s carred out by swtchng on APs wthn the LTE cell one by one untl the entre LTE cell overlaps wth WF coverage. AP actvaton sequence s based on the number of users covers by an AP, AP whch covers the most users s swtched on frst and followed by APs wth lesser users n descendng order. Fgure a shows that n general, that the average user throughput ncreases lnearly for all NSSs as backhaul capacty ncreases and startng to flatten at Mbps. The maxmum average user throughput for PDR, DyBaCS and WF are.mbps,.0mbps and.mbps respectvely at 00% WF-LTE coverage overlap and 0Mbps backhaul capacty. PDR whch has the hghest average throughput only has a margnal performance edge as compared to DyBaCS. The dfference n performances dmnshes when WF-LTE coverage overlap ncreases. WF provdes the worst average user throughput n most cases. An nterestng pont to note s for WF at Mbps backhaul capacty, ncreases n WF coverage results n a drop n the average user throughput nstead of ncrease. Ths s due to the fact that WF connects all users to WF networks regardless of ts backhaul capacty. Consequently, wth lmted WF backhaul capacty as low as Mbps, WF causes the users to suffer from low average throughput and becomng more severe when WF coverage s larger.

10 Transactons on Emergng Telecommuncatons Technologes Page 0 of (a) Average User Throughput (b) Farness For Peer Revew Fgure : NSSs performance as a functon of backhaul capacty and WF-LTE overlap percentage (Maxmum WF APs, Unform WF backhaul capacty). Fgure b shows that DyBaCS has the hghest farness for the entre range of WF-LTE overlap rato and backhaul capacty consdered. As for WF, hgher farness can be acheved wth hgher WF backhaul capacty because adequate capacty s shared amongst users. It s also found that farness of PDR s closer to DyCaBS when backhaul capacty s low but the dfference between them becomes larger as the backhaul capacty ncreases because the capacty dstrbuton of PDR s less far. At Mbps backhaul capacty and 00% WF-LTE coverage overlap, both WF and PDR acheve 0. and 0. respectvely n terms of farness, but ths s lower than 0. by DyBaCS... Effect of User Densty A hgh probablty that the number of users n a network wll vary drastcally from peak hour to off peak of the day exsts, especally n urban area. Furthermore, the number of users may also ncrease but gradually n resdental areas due to the growth n populaton. To evaluate how the NSSs under study cope wth the varaton of user densty, an evaluaton s carred out by varyng the number of users n the HetNet cell. A scenaro wth WF APs, a medum WF densty, s chosen and WF-LTE Coverage overlap s set to 00%. The number of users s ncreased from 00 to 0, n 0 user ncrements (Fgure ). (a) Average User Throughput (b) Farness Fgure : NSSs performance as a functon of Number of Users and Backhaul capacty. ( WF APs, 00% WF-LTE Coverage) Fgure shows that PDR provdes an advantage on average user throughput over DyBaCS when WF backhaul capacty values are low (.e. Mbps to Mbps) regardless of user densty. However, when the WF backhaul capacty s ncreased, the dfference n average user throughput between PDR and DyBaCS becomes neglgble. At hghest user densty wth 0 users per square klometer, average user throughput of DyBaCS s greater than PDR when WF backhaul capacty exceeds 0Mbps. WF remans the worst n provdng capacty to users. DyBaCS remans the best scheme n terms of farness for the entre range of user densty and backhaul capacty. Fgure mples that wth ncreasng number of users, PDR s actually losng ts advantage on average user throughput and farness to DyBaCS and WF respectvely, accentuated n Fgure whch depcts NSSs performance for all three WF node denstes consderng the hghest number of users (0 users). Fgure shows that wth 0 users, PDR s the worst n terms of farness despte prevous results (refer to Fgure and Fgure ) showng that PDR s the second best on farness. PDR s advantage on average user throughput s also slced to a thn margn when both number of users and WF node densty s hgh. For nstance, n Fgure, when number of WF nodes s, PDR s much superor n terms of average user throughput.

11 Farness Average User Throughput (Mbps) Page of Transactons on Emergng Telecommuncatons Technologes Number of WF Nodes WF PDR DyBaCS (a) Average User Throughput For Peer Revew Number of WF Nodes WF PDR DyBaCS (b) Farness Fgure : Performance comparson between NSSs as a functon of total WF Nodes wth 0 Users and fxed backhaul capacty of 0Mbps However, at hgher WF node densty, PDR s advantage on average user throughput becomes nsgnfcant. As a general concluson DyBaCS s good for farness whlst mantanng the average user throughput, a clear advantage when the number of users s hgh wth dense AP deployment, a typcal urban scenaro. It s adaptve to varyng number of WF nodes and varyng number of users, hghly relevant n fast changng envronments. PDR whch s a form of greedy algorthm maxmzes the average user throughput but at the expense of compromsed farness and ts advantages n cell throughput dmnsh when both number of users and AP densty are hgh. Although WF performs adequately compared to PDR when APs densty, user densty and backhaul capacty are hgh, t performs poorly otherwse and never outperforms DyBaCS n all scenaros under study... Performance on Non-unform Backhaul Capacty In another scenaro wth 00 users, backhaul capacty of APs coverng the entre HetNet are non-unformly assgned wth AP, AP, AP and AP equal to 0Mbps, 0.Mbps, 0Mbps and Mbps respectvely. Average user throughput s presented n Fgure a, where PDR has the hghest value (.Mbps) followed by DyBaCS (.Mbps) and WF (.Mbps). PDR s expected to offer hgher average user throughput as t selects the network based on the hghest physcal data rate wth the ntenton of maxmzng the average user throughput. However, t degrades the farness n terms of capacty dstrbuton among the users hghlghted n Fgure b where the farness ndex of PDR s only 0. compared to 0. by usng DyBaCS. Although the average throughput of DyBaCS s % lower than PDR, but the traded off seems to be worthwhle as farness s sgnfcantly mproved by %. WF only provdes a 0. farness ndex. (a) Average User Throughput (b) Farness Fgure : (a) Average user throughput and (b) Farness on bandwdth sharng wth non-unform WF backhaul capacty. ( Nodes, 00 users) (a) Average User Throughput (b) Farness Fgure : (a) Average user throughput and (b) Farness of bandwdth sharng wth non-unform WF backhaul capacty. ( Nodes, 0 users) Usng a smlar scenaro but by ncreasng the number of users to 0, Fgure b shows that farness ndex offered by PDR (at 0.) s the poorest amongst all the NSSs under study although as shown n Fgure a, PDR provdes the hghest

12 Transactons on Emergng Telecommuncatons Technologes Page of average user throughput. DyBaCS on the other hand provdes a good balance between average user throughput and farness. The results captured n Fgure and Fgure consstently ndcate that DyBaCS, under non-unform WF backhaul scenaros, provsons best farness to users wth mnmal penalty n the average user throughput. DyBaCS provdes the best performance on both average throughput and farness when both user densty and WF node densty s hgh (smlar to unform backhaul capacty case). Performance under non-unform WF backhaul s n agreement wth that of unform backhaul evaluaton detaled n Secton. However, t s mportant to note that changes n user locaton and dstrbuton of backhaul capacty may affect performance to a certan degree but the general trends reman.. Conclusons A backhaul capacty senstve network selecton scheme referred to as DyBaCS wthn a wreless HetNet has been presented. The performance of DyBaCS and two commonly used NSSs has been evaluated as a functon of WF backhaul capacty, WF-LTE coverage rato, WF-LTE node rato and user densty. The performance of NSSs has also been compared under unform and non-unform WF backhaul capacty dstrbutons. Results show that the proposed DyBaCS scheme provdes the best farness whlst preservng the average user throughput over all scenaros. DyBaCS s a hghly scalable NSS as compared to PDR and WF n scenaros wth varyng number of users, WF nodes and WF backhaul capacty. Future work needs to consder more realstc proportonal farness capacty sharng schemes. The use of hgher capacty LTE base statons and IEEE0.n WF also needs to be studed. Besdes, evaluaton under dfferent traffc types also needs to be addressed. Acknowledgment For Peer Revew The work s supported by Mnstry of Scence, Technology and Innovaton of Malaysa under the Scence Fund project code SF00. References. The LTE capacty shortfall: Why small cell backhaul s the answer, Avat Networks, Retreved th May 0 from Small cell market status Feb 0, Informa telecoms & meda, Retreved nd October 0 from Small cell operators face myrad operatonal and fnancal challenges, Infonetcs Research, Retreved st Oct 0 from Mark Prscaro (th May 0), Telecom New Zealand and Ruckus Wreless Transform Tradtonal Phone Booths nto Super Fast W-F Hotspots, Ruckus Wreless, Retreved th May 0 from Fretde Wreless Mesh Solutons for TELCOS: Access & Small Cell Backhaul, Karam F W, Jensen T. Performance analyss of rankng for QoS handover algorthm for selecton of access network n heterogeneous wreless networks. st Internatonal Conference oncomputer Communcatons and Networks (ICCCN), 0 July- Aug 0:-.. A Handa. Moble Data Offload for G Networks: A Whte Paper. Oct J Ne, J Wen, Q Dong, Z Zhou. A seamless handoff n IEEE0.a and IEEE0.n hybrd networks, n proc. Int. Conf. Commun. Crcuts Syst 00, : -.. J Roy, V Vadeh, and S Srkanth. Always best-connected QoS ntegraton model for the WLAN, WMAX heterogeneous network. In IEEE Frst Internatonal Conference on Industral and Informaton Systems, - Aug 00: Y Bejerano, S J Han, and L E L. Farness and Load Balancng n Wreless LANs Usng Assocaton Control, IEEE/ACM Transactons on Networkng 00; ():0-.. Judd G, Steenkste P. Fxng 0. access pont selecton. ACM SIGCOMM Computer Communcaton Revew 00; (): -.. D Kumar, E Altman, and J M Kelf. Globally optmal user-network assocaton n an 0. WLAN and G UMTS hybrd cell. Internatonal Teletraffc Congress, Ottawa, Canada, June - 00: -.. K Premkumar and A Kumar. Optmum Assocaton of Moble Wreless Devces wth a WLAN-G Access Network, Proc. IEEE Int l Conf. Comm. (ICC 0), - June 00: S. Sngh, H. S. Dhllon, and J. G. Andrews. Offloadng n heterogeneous networks: Modelng, analyss, and desgn nsghts, IEEE Trans. Wreless Communcatons 0; (): -.. P L, J Kong, S H Km, H B Jung, X L Nu, D K Km. Power allocaton wth max-mn farness for multcast n heterogeneous network, th Internatonal Conference on Advanced Communcaton Technology (ICACT), - Feb 0: 0-0. P Xue, P Gong, J H Park, D Y Park, D K Km. Rado resource management wth proportonal rate constrant n the heterogeneous networks, IEEE Transactons on Wreless Communcatons 0; (): Y Bejerano and S J Han. Cell Breathng Technques for Load Balancng n Wreless LANs. IEEE Tranctons on Moble Computng 00; (): -.. H Velayos, V Aleo, and G Karlsson. Load Balancng n Overlappng Wreless LAN Cells, Proc. IEEE Internatonal Conference on Communcatons, 0- June 00: -.. Pe X, Jang T, Qu D, Zhu G & Lu J. Rado-resource management and access-control mechansm based on a novel economc model n heterogeneous wreless networks. IEEE Transactons on Vehcular Technology 00, (): Zhuo X, Hua S, Gao W & Cao G. An Incentve Framework for Cellular Traffc Offloadng. IEEE Transactons on Moble Computng 0; (): -.. Yang Z, Yang Q, Fu F & Kwak K S. A novel load balancng scheme n LTE and WF coexsted network for OFDMA system. Internatonal Conference on Wreless

13 Page of Transactons on Emergng Telecommuncatons Technologes Communcatons & Sgnal Processng (WCSP), - Oct 0; -.. F Bar and V C M Leung. Automated network selecton n a heterogeneous wreless network envronment. IEEE Network 00; (): 0.. H Hu, W Zhou, S Zhang, J Song. A Novel network selecton algorthm n next generaton heterogeneous network for modern servce ndustry. IEEE Asa-Pacfc Servces Computng Conference, - Dec 00: -.. Galeana-Zapen H, Ferrus R. Desgn and Evaluaton of a Backhaul-Aware Base Staton Assgnment Algorthm for OFDMA-Based Cellular Networks. IEEE Transactons on Wreless Communcatons 00; (0): -.. Pahlavan K, & Levesque A H. Wrless Informaton Networks, nd Edton, John Wley & Sons, 00.. P Bender et al. CDMA/HDR: A Bandwdth Effcent Hgh-speed Wreless Data Servce for Nomadc User. IEEE Communcaton Magazne 000; (): 0.. Gerasmenko M, Moltchanov D, Florea R, Andreev S, Koucheryavy Y, Hmayat N, Yeh S-p. & Talwar S. Cooperatve Rado Resource Management n Heterogeneous Cloud Rado Access Networks. IEEE Access 0; : -0.. Yang C, L J & Anpalagan A. Cooperatve barganng game - theoretc methodology for G wreless heterogeneous networks. Transactons on Emergng Telecommuncatons Technologes 0; (): 0-.. Bredel M & Fdler M. A measurement study of bandwdth estmaton n IEEE 0. g wreless LANs usng the DCF. NETWORKING 00 Ad Hoc and Sensor Networks, Wreless Networks, Next Generaton Internet; : -. Sprnger. For Peer Revew 0. Yongmn Cho, Hyun Wook J, Jae-yoon Park, Hyun-chul Km, Slvester J A. A W network strategy for moble data traffc offloadng. IEEE Communcatons Magazne 0; (0): -.. Tranzeo Wreless Technologes Inc. Example Communty Broadband Wreless Mesh Network Desgn, Verson., 0June 00.. NanoStaton, Ubqut Networks, A Tng, D Cheng, K H Kwong, I Andonovc. Optmzaton of Heterogeneous Mult-rado Mult-hop Rural Wreless Network. IEEE th Internatonal Conference on Communcaton Technology 0, ChengDu Chna, - Nov 0: -.. GPP, Evolved Unversal Terrestral Rado Access (E- UTRA); Rado Frequency (RF) system scenaros (Release 0), GPP TR. V ITU-R Report M.-: Gudelnes for evaluaton of rado nterface technologes for IMT-Advanced, December 00.. M Petrova, P Ma ho nen, and J Rhja rv. Connectvty analyss of clustered ad hoc and mesh networks, In Proceedngs of IEEE GLOBECOM, Martnque -0 Nov 00: -.. R Jan, A Durres, and G Babc. Throughput farness ndex: an explanaton, ATM Forum/-00, Feb..

14 Transactons on Emergng Telecommuncatons Technologes Page of Scalablty Study of Backhaul Capacty Senstve Network Selecton Scheme n LTE-WF HetNet Alvn Tng, Davd Cheng, Kae Hsang Kwong Wreless Communcaton, MIMOS Berhad, K.L, Malaysa. {kee.tng, ht.cheng, kh.kwong}@mmos.my Abstract Wreless Heterogeneous Network (HetNet) wth small cells presents a new backhaulng challenge whch dffers from those of experenced by conventonal macro-cells. In practce, the choce of backhaul technology for these small cells whether fber, xdsl, pont to-pont and pont-to-multpont wreless, or mult-hop/mesh networks, s often governed by avalablty and cost, and not by requred capacty. Therefore, the resultng backhaul capacty of the small cells n HetNet s lkely to be non-unform due to the mxture of backhaul technologes adopted. In such an envronment, a queston then arses whether a network selecton strategy that consders the small cells backhaul capacty wll mprove the end users usage experence. In ths paper, a novel Dynamc Backhaul Capacty Senstve (DyBaCS) network selecton schemes (NSS) s proposed and compared wth two commonly used network NSSs, namely WF Frst (WF) and Physcal Data Rate (PDR) n an LTE-WF HetNet envronment. The proposed scheme s evaluated n terms of average connecton or user throughput and farness among users. The effects of varyng WF backhaul capacty (unform and non-unform dstrbuton), WF-LTE coverage rato, user densty and WF access ponts (APs) densty wthn the HetNet form the focus of ths paper. Results show that the DyBaCS scheme generally provdes superor farness and user throughput performance across the range of backhaul capacty consdered. Besdes, DyBaCS s able to scale much better than WF and PDR across dfferent user and WF denstes. Ivan Andonovc CIDCOM, Dept. EEE, Unversty of Strathclyde, Scotland, UK.andonovc@eee.strath.ac.uk For Peer Revew Keywords - Hetrogeneous Network, Network Selecton, LTE, WF, Traffc Offload, Backhaul Capacty. Introducton The ncreasng pressure for moble operators to offload data traffc from ther G, LTE or WMAX networks to small cell networks [] [] ndcates that future moble broadband networks wll largely be heterogeneous. Ths mgraton s further fueled by the avalablty of mult-rat (Rado Access Technology) whch allows user devces to connect to dfferent wreless networks such as G, LTE, WMAX, WF ether one Capacty and throughput are used nterchangeably throughout artcle wth the detal defnton n secton. * A shorter verson of ths artcle s presented n []. Ths artcle ncludes substantal revsons, enhancements and extensons to []. K. D. Wong Danel Wreless LLC Palo Alto, CA, USA dwong@danelwreless.com at a tme or smultaneously. Deployment of small cells such as WF rases new backhaul challenges for operators. There are only two broad choces as far as backhaul s concerned, wrelne and wreless backhaul. Due to ntensve engneerng work requred, hgh cost and regulatory barrers, fxed lne solutons such as fber, cable, copper or xdsl are not ubqutously avalable. Further, a relatvely large number of WF hotspots may prove too costly for operators to backhaul wth wred optons. In such stuatons, the operator may nstead ncreasngly rely on pont-to-pont and pont-to-multpont wreless solutons. However n most scenaros, a mxture of backhaul technologes s expected, as operators wll adopt the most sutable backhaul soluton for small cells consderng the cost and avalablty [] (Fgure ). Wth the maturty of multhop mesh networks, t may also serve as a potental canddate [] []. Currently, WF APs are typcally backhauled through dfferent types of technologes whch offer throughput capacty rangng from several mega bt per second (Mbps) to tens of Mbps []. Backhaulng APs usng dfferent technologes wthn the HetNet leads to non-unform AP capacty dstrbuton. The most wdely deployed IEEE0.n WF technology whch provsons a peak physcal data rate of 00Mbps. Due to that most exstng fxed backhaul servces are not able to offer suffcent capacty for these WF APs to realze ther full potental. Therefore consderaton of WF backhaul capacty s nevtable durng traffc offload decson makng. Fgure : LTE-WF Heterogeneous Network wth dfferent backhaul optons... Related Work To reduce data traffc pressure over moble networks, alternatve networks such as WF are preferred by moble operators whenever possble []. As report n [], most WF-enabled smartphones are confgured wth WF Frst

15 Page of Transactons on Emergng Telecommuncatons Technologes network selecton scheme by default to gve WF hgher prorty over the cellular nterface for data transmssons. Network selecton strateges for WMAX-WF network whch s predomnantly drven by data rate are reported n [] and [0]. Ths knd of network selecton strateges lead to poor user experences [] and causes unbalanced load dstrbuton amongst access networks []. Several studes [-] have proposed the use of Network Selecton Schemes (NSSs) to optmze network performance. The work by [] consders a globally optmal user-network assocaton scheme n a WLAN-UMTS hybrd cell. In [], a heurstc greedy search algorthm that maxmzes total user throughput n a heterogeneous wreless access network comprsng WF APs and G BSs s proposed. Both these studes adopt a smplfed WLAN model by assumng only one transmsson rate. Posson pont process (PPP) theory and stochastc geometry method are used n [] to model traffc offloadng n a mult RAT heterogeneous wreless network. The authors propose a method to determne the optmum percentage of the traffc that needs be offloaded n order to maxmze network coverage whle meetng user requrements. In that work however, no network selecton algorthm s proposed. For Peer Revew Farness performance s consdered n [-] where [] focuses on ensurng max-mn farness for multcast n Orthogonal Frequency Dvson Multple Access (OFDMA)- based wreless heterogeneous networks. A proportonal user rate based rado resource management strategy s nvestgated n [] on LTE-WF HetNet, where a suboptmal network selecton algorthm s ntroduced to mprove the mnmum normalzed user rate and farness. Bejerano et al. [] proposes changes to the transmsson power of AP beacon messages n order to mnmze the load n congested APs and produces an optmal max-mn load balancng strategy. A load balancng scheme for overlappng wreless LAN cells s reported n []. However, the work ams to balance the throughput of APs and not the farness amongst users. NSSs that consder QoS are reported n [] [] []. Network selecton based on multple parameters such as cost, bandwdth and QoS parameters ncludng packet loss, jtter and delay s reported n []. However, the study focuses only on general heterogeneous networkng and no specfc type of technology s smulated. Smlarly, the work n [] and [] nvestgate access network selecton for optmal servce delvery and QoS to users respectvely. However the overall HetNet performance and farness s not consdered. Load balancng n Cellular and WLAN HetNet s reported n [0] [] and []. In [0], a jont access-control strategy s desgned for sharng of the rado resource and load balancng between CDMA Cellular Network and WLANs by consderng user preferences. Bandwdth allocaton s optmzed by maxmzng the aggregated socal welfare of the WLANs under nterference-constrant envronment. However, the method used to balance the load amongst moble nodes s not dsclosed. The work n [] looks nto the trade-off between the amount of traffc beng offloaded and users satsfacton. An ncentve framework s proposed to motvate users to use delay tolerance WF networks for traffc offloadng. Yang et al. n [] proposes a load balancng scheme that ams to balance the network load between the LTE network and WF hotspots consderng access pattern of UEs. Bejerano et al. [] consders backhaul capacty durng AP selecton, whle [] proposes a backhaul-aware base staton (BS) selecton algorthm. Although backhaul-aware network selecton scheme have been explored n these works, ther scope s lmted to homogeneous wreless networks. In ths paper, a Dynamc Backhaul Capacty Senstve (DyBaCS) NSS s proposed for LTE-WF HetNet. Ths scheme not only consders access lnk throughput but also avalable backhaul capacty n order to preserve farness amongst users. The proposed scheme s compared wth two commonly used NSSs namely WF Frst (WF) and Physcal Data Rate (PDR). Ths paper nvestgates farness and average user throughput performances across WF backhaul capacty rangng from Mbps to Mbps. The rest of the paper s organzed as follows. Secton descrbes the proposed DyBaCS network selecton algorthm as well as WF and PDR schemes. Secton detals the smulaton approach, smulaton parameters and assumptons made. Results are dscussed n Secton followed by conclusons n Secton.. Exstng and Proposed Network Selecton Schemes Ths secton descrbes the smulaton approach smulaton parameters and assumptons used n the study. The notatons used are lsted n TABLE I. Notaton, SNR NLOS OF EIRP WF DyBaCS PDR MAC UE TABLE I : NOTATIONS Descrpton number of clusters for user dstrbuton wdth and heght of user dstrbuton clusters number of users n a cluster sgnal to nterference and nose rato sgnal to nose rato WF receve power by user u WF nterference power nose floor average user throughput WF downlnk physcal transmsson rate to users lnk throughput effcency measured at the IP layer maxmum downlnk throughput achevable by a LTE user path loss n db dstance n meters Non-lne-of-sght overbookng factor effectve sotropc radated power WF Frst network selecton scheme Dynamc Backhaul Capacty Senstve network selecton scheme Physcal Data Rate Based network selecton scheme medum access control user equpment system throughput of AP LTE system throughput wthn the HetNet total number of users n AP

16 Transactons on Emergng Telecommuncatons Technologes Page of ,, total number of users n a LTE cell total number of users n HetNet access lnk throughput from AP to user access lnk throughput from LTE BS to user backhaul capacty of AP n Mbps average AP users throughput wth lmted backhaul capacty average AP users throughput wth suffcent backhaul capacty effectve user throughput, Ω.. Network Capacty Model estmated throughput f user n s connected to AP estmated throughput f user n s connected to LTE BS lst of hgher speed connectons (amongst WF and LTE nterfaces for a user) for all users n throughput set that contans all users n the HetNet... Sngle WF AP wth Max-mn Farness For Peer Revew In a mult-rate WF network, users wth slower lnk speed tend to occupy more spectrum resource (n terms of transmt tme) than hgher speed users for the same amount of data sent. Such a bandwdth sharng scenaro amongst all users wthn a sngle AP coverage has been modelled. Suppose a total of users are connected to an AP and each s supported by a data rate, n accordance to ther level. Thus, user receves transmsson slots at rate bps, where =,... Assumng the channel access probablty s and t exhbts the effect of slots assgnment, whch s nversely proportonal to user data rate. Let be the number of slots allocated to user, where = /, wth beng an arbtrary constant whch wll be cancelled off eventually. In ths case, f user packet sze s assumed to be the same, the AP throughput at the physcal layer can be calculated as [] []: = Substtutng = nto Eqn (); = = = Snce the sum of by all user s =, Eqn () can be further smplfed to: = The average physcal layer throughput per user s calculated by dvdng Eqn () wth the total number of users Snce far resource sharng s assumed, whch n turn mples that the packet sendng frequency of every user s the same, the of a user can also be wrtten as : () () () = = The model facltates max-mn farness [] [] behavor n a mult-rate system where all users are allocated an equal amount bandwdth resource. Ths characterstc s representatve of WLAN Dstrbuted Coordnated Functon (DCF) [0] where all users are offered a far medum access opportunty. Example : Assume two users are connected to an AP wth supported data rate of = Mbps and = Mbps respectvely. The number of tme slots assgned s nversely proportonal to data rate hence = = and = =, where s an arbtrary constant. The channel access probablty of user and user are represented by and. Snce both have a far chance to transmt to the AP or vce versa, = =. Wth both users takng turn to transmt packets and f ther packet szes are the same, the tme taken by each user to transmt a packet can be represented by Fgure. = () Fgure : Tme slots requred by user and user consderng far throughput From Fgure, User takes more tme than User n order to mantan throughput farness. In other words, User s beng penalzed n terms of tme slot farness, whch s the characterstc of WF DCF system. The average throughput for both users can be calculated usng Eqn () as follows: = = () By substtutng the values of,, and nto Eqn (), the average throughput for both users can be calculated as. Mbps. Smlarly, wthn a sngle WF network, the average IP layer throughput per user (Eqn ()) s calculated by multplyng the physcal data rate n Eqn () by a correspondng throughput effcency factor gven n TABLE V: = = The accuracy of the model (mplementaton of Eqn ()) s verfed together wth the IEEE0.g WF models (n ()

17 Page of Transactons on Emergng Telecommuncatons Technologes secton.) usng the QualNet event-drven smulator (Verson.) and the results are found to be very smlar.... LTE wth Max-Mn Farness In LTE, resource s assgned to users n forms of Physcal Resource Blocks (PRB) consstng of many Resource Elements. The same max-mn far bandwdth sharng approach s adopted where n the LTE case, more PRBs are assgned to users experencng worse channel behavor to ensure farness. Ths assumpton s reasonable snce the LTE Medum Access Control (MAC) scheduler has not been fully defned n the standards. In order to smplfy the study, resource element allocatons n LTE are approxmated as tme fracton allocaton n a TDMA manner as modeled n [] and the average user throughput s defned by Eqn (), a straghtforward modfcaton from Eqn (): = For Peer Revew where s maxmum lnk throughput achevable by LTE user and s the total number of LTE users... Network Selecton Schemes In a heterogeneous wreless network comprsng two or more technologes, user throughput farness needs to be consdered n two aspects, ntra-network farness and nternetwork farness. Intra-network farness can be provded by AP or LTE BS to ts assocated users as the task s confned locally. Wth max-mn far capacty sharng of WF and LTE network (Eqn () and Eqn ()), farness s achevable amongst users under the same AP or BS. However, far capacty sharng across the entre HetNet s not guaranteed and s strongly dependent on the mplemented NSSs. The proposed DyBaCS s compared wth two commonly used NSSs namely WF Frst (WF) and Physcal Data Rate (PDR), the characterstcs of whch are as follows:... WF Frst (WF) WF Frst (WF) connects a user to an AP whenever WF coverage s avalable. In other words, a user wll never connect to a LTE network when there s WF coverage. Ths approach s adopted by most smart phones and tablets connecton manager by default as the preferred data connecton mode. In addton, ths mode s also promoted by some moble operators as a means to offload traffc from moble networks [] [].... Physcal Data Rate (PDR) PDR chooses the network based on the Physcal data rate of the RAT avalable to the user [] [0]. Here the physcal data rates provded by LTE and WF are compared and the RAT wth hgher physcal data rate s chosen. Snce PDR tends to assgn more bandwdth to the users wth better lnk capacty, t compromses user farness, though the overall throughput performance mght be good. ()... Proposed Dynamc Backhaul Capacty Senstve (DyBaCS) scheme DyBaCS s manly proposed to preserve farness whle maxmzng HetNet throughput. Thus DyBaCS throughput performance may not outperform PDR (whch s optmum n mantanng HetNet throughput), but t s very close to PDR n most cases (Secton ). In the study, a sngle LTE network s assumed wth denotng the total number of WF APs n the HetNet and denotng the ndex of the network,.e. network = s the -th WF network, whle, = represents the -th user n the HetNet and s the total user n entre HetNet. Total number of users n AP and LTE network s represented by and respectvely. Before explanng the DyBaCS algorthm n detal, Algorthm ; the User Throughput Estmaton Flow (UTEF) algorthm, whch enables the estmaton of WF user throughputs, and LTE user throughputs, s frst presented as follows: Algorthm : Users Throughput (, ) Estmaton Flow (UTEF) a) WF UTEF: ) Let u = {,,, } } s number of WF users n Network ) Average user throughput s : = ; Eqn () ) System throughput for network s: For = A) If ), = h, =, B) Elsef < ), = / ) f,, a), =,, < h ) If, >, a), =,, < h b) LTE UTEF: ) Let u = {,,, } s number of users n LTE Network ) Average user throughput s : = ; Eqn () ) Average user throughput consderng OF s:, =,, <, For WF UTEF (Algorthm ), the calculaton of effectve WF user throughput, s based on user access lnk throughput,, AP backhaul capacty and Overbookng Factor (OF). Lnk throughput, (or equvalent to n Eqn () and s lsted n TABLE V) of user s predomnately affected by the dstance from the AP, channel qualty and other channel condtons such as nterference. Backhaul capacty s defned as the actual avalable backhaul capacty to AP, whether t s wred or wreless backhaul. Effectve user throughput s lmted by both

18 Transactons on Emergng Telecommuncatons Technologes Page of factors. In practce, OF s normally consdered as not all the users access the channel at the same tme []; by ncludng OF the perceved throughput from the users pont of vew can be calculated. The calculaton of effectve user throughput n WF UETF can be explaned n detal wth the ad of the scenaro shown n Fgure, where users are connected to AP. User data rate and lnk throughput, are lsted n TABLE II. For Peer Revew Fgure : AP wth users under ts coverage TABLE II : USER DATA RATE AND LINK THROUGHPUT IN Fgure User, u, = 0. =. 0. =. 0. =. 0. =. Step and Step n Algorthm estmate the average WF user throughput usng Eqn () and the average user throughput can be calculated as: = = = = = =. M () Multplyng the average user throughput by the total number of users, as n Step, yelds the total system throughput of AP: = () In the scenaro, =. =. Mbps. As n Eqn (), s affected by lnk speed of all users n network ; therefore t s hghly dependent on users dstrbuton. represents the requred backhaul capacty for AP to realse ts full access capacty. If the backhaul capacty s suffcent to support the maxmum capacty from the AP to clents such = h = that, then all users wll enjoy a throughput of. However, f the backhaul capacty s the bottleneck,, the avalable backhaul capacty s shared evenly to all users and average user throughput n such scenaro s lmted to a value, (Eqn (0)) whch s less than., = / (0) It s mportant to note that users wll not secure a throughput hgher than even at backhaul capactes greater than due to the restrcton mposed by the WF physcal and MAC layer capablty. Under the assumpton of smultaneous channel access, or, represents the average user throughput for both suffcent and lmted backhaul capacty cases. In Fgure, assumng that backhaul capacty = 0 s less than =., the actual average throughput for the users s lmted to, = Otherwse, each user wll enjoy. = =. Mbps. =. Mbps f In order to smplfy the explanaton of Algorthm, an OF = s adopted for scenaro depcted n Fgure. Suppose = Mbps where, the effectve average throughput, of user s only lmted by ts lnk throughput,. Step A () places a constrant to ensure that the value of does not exceed,. TABLE III shows that effectve user throughput, s the mnmum value between and,. Note that the effectve average throughput for User and User s lmted to ther lnk throughput whch s. Mbps and. Mbps respectvely. User, TABLE III : EFFECTIVE USER THEROUGHPUT, UNDER CONDITION.,, Lkewse, wth lmted backhaul capacty, Step B () and Step B () ensure that, s bound by both, and, whchever s smaller. The result s shown n TABLE IV. TABLE IV : EFFECTIVE USER THROUGHPUT, UNDER CONDITION. User,,,

19 Page of Transactons on Emergng Telecommuncatons Technologes In short, Step mposes logcal consderatons to the determnaton of the effectve user average throughput, takng nto consderaton backhaul capacty, user lnk speed and OF. Smlarly, the LTE user throughput can also be estmated usng the LTE UTEF approach. In ths paper, LTE backhaul capacty s always assumed to be suffcent. Therefore n Step, the only constrant for user throughput n the LTE network s the access lnk throughput,. The DyBaCS NSS (Algorthm ) assumes that ntally, there s no user connected to the HetNet. Users are admtted to the HetNet one by one and ther servcng network s determned by the NSS. Step ntalzes varables Ω,, and, where Ω s a lst holdng the hgher speed connectons between WF and LTE nterfaces to users, s the set contanng all users n the HetNet, s the lst of users connected to the WF AP and s the lst of users connected to the LTE network. For Peer Revew In Step, the access lnk wth the hghest throughput between user to LTE (, ) or WF (, ) s chosen and placed nto Ω, Ω represents the throughput value for user. All users are able to connect to at least the LTE network whle access to WF depends on avalablty of WF coverage. Hence = 0, denotes the connectvty of user to AP, = means connecton s possble, 0 means the opposte. Snce mult-homng s not consdered, every user s only allowed to connect to one network at a tme. Step assgns all users wth no WF access to the LTE network and excludes those users from set. The network selecton parameter 0, ndcates the choce of user ; = ndcates that user s connected to network and value 0 means the opposte. The remanng users wthn set whch have not been assgned to any network are subjected to network selecton; they can ether assgned to WF or LTE. Network selecton for those users s addressed n Step n order to optmze the network performance. Step (a) ensures the user wth the hghest lnk throughput wthn set (referred to as user ) s consdered frst. In Step (b) and Step (c), the achevable throughput of user (consderng access lnk speed, AP backhaul capacty and OF) on WF AP and LTE s estmated usng WF UTEF and LTE UTEF and represented by, and, respectvely. The throughput estmaton s executed assumng that user s added to the correspondng WF or LTE network. Therefore, durng the throughput estmaton, the total number of users connected to AP s assumed to be user plus the total number of exstng users wrtten as and smlarly the total number of users n the LTE network s. The achevable throughput for user on the WF and LTE network s then assgned to and respectvely. User s subsequently assgned to the network that offers the hghest throughput and the correspondng or value s set accordng to Step (d). The total number of users connected to ther respectve -th WF network or LTE network s then updated. Fnally set s updated by excludng user n Step (e) and the Step processes are repeated untl all users are servced. Algorthm : DyBaCS ) Intalzaton a) Ω =, and =,,, b) =, = 0,, ; = ) For = a) Ω,,,, = 0,, ) For = a) f user satsfyng = 0, =,,. =. = ) whle a) fnd where Ω Ω for all and b) Estmate user throughput, n -th WF Network assumng user n s ncluded to the network,.e. ; Usng WF UTEF (Algorthm a)., c) Estmate user throughput, n LTE Network assumng user n s ncluded to LTE Network,.e. ; Usng LTE UTEF (Algorthm b);., d) If. =. = Else. = v. = e) =. Parameters, Assumptons and Smulaton Approach The secton descrbes the smulaton approach, smulaton parameters and assumptons used... WF Model TABLE V presents the parameters used n the WF IEEE0.g model. The recever senstvty values per modulaton and codng scheme (MCS) for WF recevers are taken from []. The throughput effcency, the rato of actual IP layer throughput aganst physcal data rate and the actual IP layer throughput of each MCS scheme are obtaned from the QualNet smulator assumng fxed packet sze of 000 Bytes wth constant bt rate traffc. Index MCS TABLE V : IEEE0.G PARAMETERS Recever Data Throughput Senstvty Rate Effcency (dbm) (Mbps) () Throughput (Mbps) BPSK/ BPSK/ QPSK/ QPSK/ QAM/ QAM/ QAM/ QAM/

20 Transactons on Emergng Telecommuncatons Technologes Page 0 of The path loss model n Eqn () s derved from feld measurement detaled n [] :.. LTE Model = () LTE throughput s calculated based on the throughput plot by GPP [] shown n Fgure. In the smulaton, SINR rato at a recever s used to calculate the achevable throughput. In order to calculate the receved power, the ITU recommended LTE Urban Macro (UMa) non-lne-of-sght (NLOS) path loss model s used []. Throughput (bts/sec/hz) QPSK / QPSK / QPSK / QPSK / QPSK / QPSK / QPSK / For Peer Revew QAM / QAM / QAM / SNR (db) Fgure : LTE throughput vs. SNR for dfferent Modulaton and Codng Schemes (MCS) used n the model.. Stochastc User Placement Model QAM / QAM / QAM / A stochastc node locaton model s used to poston the users n the HetNet. The authors n [] found that ths model can represent the users locatons around WF AP n a cty or urban envronment. Here users are assumed to be dstrbuted around cluster centers. Two spatal dstrbutons model are adopted where the frst dstrbuton s used to generate the numbers and locatons of the cluster centers. The second dstrbuton s then used for postonng the number of users around each center. The ntal cluster center dstrbuton s generated randomly wth total number of cluster centers equal to. Subsequently, a bvarate Gaussan dstrbuton wth covarance matrx =, s used to generate actual user locatons around the cluster centres. The sze and shape of the cluster s characterzed by the parameters and (Fgure ). The number of users per cluster s drawn from a Posson dstrbuton wth ntensty. Parameters, and are the same for every cluster. In the smulaton, ntally 00 users are placed n an area of square klometre wth number of clusters = 0, cluster sze = 0 and = =. Subsequently 0 users are added each tme by ncreasng number of cluster by fve whle keepng the number of users per cluster and cluster dmenson unchanged, untl the total number of users reaches 0 (Fgure ). Snce all users are tabulated n an area of square klometre, the terms the number of users and user densty are used nterchangeably n the rest of ths paper. Fgure : User placement wth total number of clusters = 0, cluster sze = 0 and σ = Fgure : User placement from 00 users to 0 users wth 0 users added every tme, maxmum =, cluster sze = 0 and σ =.. Placement of WF Access Ponts Fgure : WF APs placement wthn HetNet that comprses the scenaros wth, and WF APs In the Matlab model, WF APs are placed wthn a macro LTE cell accordng to three selected topologes shown n Fgure. These WF topologes enable the NSSs to be evaluated as a functon of WF-LTE node ratos (or WF node denstes). By controllng the APs transmt power, these WF topologes can gve the same coverage sze as the macro LTE cell. For example, Fgure a shows the coverage plot for APs, whle the overlay of both WF and LTE cell (Fgure b) that forms the HetNet s llustrated n Fgure c. WF coverage plots for and APs are shown n Fgure a and Fgure b respectvely. Although there s no lmt on the varaton topologes whch can be evaluated, the selected topologes s beleved to be able to provde a good nsght on the performance of NSSs under dfferent WF-LTE node ratos.

21 Page of Transactons on Emergng Telecommuncatons Technologes (a) (b) For Peer Revew (c) Fgure : Network coverage plot based on data rate wth x and y axs showng coverage sze n meter; a) -WF-Nodes networks wth access channel shown n parentheses, b) LTE network and c) HetNet (LTE+WF) wth 00 users (a) Fgure : WF coverage plot based on data rate wth x and y axs showng coverage sze n meter; a) -WF-Nodes networks, b) -WF-Nodes networks; WF access channel shown n parentheses.. WF Access Channel and Interference On WF access channel, three non-overlappng channels wth channel number, and are used (channel number s stated on top of each AP n Fgure and Fgure ). To calculate SINR, the smulated area s dvded nto -by- square meter grds. Snce non-overlappng channels are used, only cochannel nterference s consdered. In each grd, an effectve SINR s derved as: = (b) () where, s the receved power of user from the servng AP located n a grd, s total number of co-channel nterferer APs n range, s the nterference power at the recever and s the nose floor. Effectve SINR obtaned s then used to map user data rate and hence user throughput calculaton n WF networks AP() Fgure 0: -WF-Nodes coverage plot wth co-channel nterference Fgure 0 shows the coverage plot of WF nodes wth cochannel nterference. The nterference has resulted n a smaller effectve WF coverage area as compared to Fgure a, whch has a better channel plan... WF and LTE backhaul AP() AP() AP() AP() AP() In the study, WF backhaul capacty s vared from Mbps up to Mbps untl the throughput of AP saturates (Secton ). Two backhaul scenaros are assumed when evaluatng the NSSs; ) unform WF backhaul capacty and ) non-unform WF backhaul capacty throughout the HetNet. The LTE base staton (BS) backhaul capacty s always assumed to be suffcent... General Parameters and Assumptons AP() TABLE VI summarzes the smulaton parameters used. Only the downlnk performance s nvestgated n the paper..ghz s used for LTE as t s the frequency band allocated n Malaysa. A fxed nterference margn of db s assumed for the LTE User Equpment (UE). TABLE VI : WIFI AND LTE SIMULATION PARAMETERS Unts WF g LTE Frequency band GHz.. Channel bandwdth MHz 0 0 Max EIRP dbm,, Rx antenna gan db 0 Antenna dversty gan db Nose Fgure db Not requred 0 Packet sze Bytes 000 WF backhaul capacty Mbps LTE backhaul capacty Mbps Suffcent capacty assumed User Informaton Overbookng Factor, OF - 0: User densty Users/sqkm 00, 0, 00, 0 Recever antenna gan of WF and LTE UE s assumed to be db and 0 db respectvely. The assumpton on traffc type has been descrbed n Secton... From [], the Overbookng Factor (OF) s a desgn choce drven by actual user behavor n the deployed area. OF that vares from : to 00: has been reported by varous ISPs and the lower the

22 Transactons on Emergng Telecommuncatons Technologes Page of Fgure : HetNet average user throughput as a functon of WF backhaul capacty. ( WF APs, 00% WF-LTE overlap, Unform WF backhaul capacty) For Peer Revew value the better the servce guarantee. A factor of 0: n adopted to represent a relatvely heavy usage scenaro. User densty s vared from 00 users to 0 users per square km.. Results and Analyss.. Effect of Varyng Backhaul Capacty Unformly Two performance metrcs namely average user throughput and user throughput farness n the HetNet cell are used to evaluate the performance of the NSSs. Farness s derved usng Jan farness ndex n the form of, /, []. Frst the performance of all NSSs s evaluated as a functon of WF backhaul capacty from Mbps to Mbps wth 00% WF-LTE coverage overlap and WF APs (as n Fgure c). Fgure shows that average user throughput of PDR and DyBaCS are smlar over the entre range of backhaul capacty and WF has the lowest average user throughput. The plots plateaus when backhaul capacty reaches 0Mbps for all NSSs as that s the maxmum access throughput achevable by WF (IEEE 0.g). The total WF access throughput also depends on user dstrbuton as slower users slow down the entre network. Fgure evaluates the farness n terms of achevable throughput per user. Result shows that average user throughput of PDR and DyBaCS are smlar over the entre range of backhaul capacty whle WF has the lowest average user throughput. DyBaCS outperforms the rest n terms of farness and WF exhbts the worst farness performance. Fgure : Farness on bandwdth sharng as a functon of WF backhaul capacty. ( WF APs, 00% WF-LTE overlap, Unform WF backhaul capacty).. Effect of WF-LTE Overlap Rato Wthn a HetNet cell Snce the coverage overlap between WF and LTE s lkely to vary n practce, t s therefore mportant to nvestgate how NSSs perform n dfferent overlap condtons. Here the coverage area s defned as a percentage e.g. % means % of LTE coverage s also covered by WF and 00% means all LTE coverage s overlapped by WF. The smulaton s carred out by swtchng on APs wthn the LTE cell one by one untl the entre LTE cell overlaps wth WF coverage. AP actvaton sequence s based on the number of users covers by an AP, AP whch covers the most users s swtched on frst and followed by APs wth lesser users n descendng order. Fgure a shows that n general, that the average user throughput ncreases lnearly for all NSSs as backhaul capacty ncreases and startng to flatten at Mbps. The maxmum average user throughput for PDR, DyBaCS and WF are.mbps,.0mbps and.mbps respectvely at 00% WF-LTE coverage overlap and 0Mbps backhaul capacty. PDR whch has the hghest average throughput only has a margnal performance edge as compared to DyBaCS. The dfference n performances dmnshes when WF-LTE coverage overlap ncreases. WF provdes the worst average user throughput n most cases. An nterestng pont to note s for WF at Mbps backhaul capacty, ncreases n WF coverage results n a drop n the average user throughput nstead of ncrease. Ths s due to the fact that WF connects all users to WF networks regardless of ts backhaul capacty. Consequently, wth lmted WF backhaul capacty as low as Mbps, WF causes the users to suffer from low average throughput and becomng more severe when WF coverage s larger.

23 Page of Transactons on Emergng Telecommuncatons Technologes (a) Average User Throughput For Peer Revew (b) Farness Fgure : NSSs performance as a functon of backhaul capacty and WF-LTE overlap percentage (Maxmum WF APs, Unform WF backhaul capacty). Fgure b shows that DyBaCS has the hghest farness for the entre range of WF-LTE overlap rato and backhaul capacty consdered. As for WF, hgher farness can be acheved wth hgher WF backhaul capacty because adequate capacty s shared amongst users. It s also found that farness of PDR s closer to DyCaBS when backhaul capacty s low but the dfference between them becomes larger as the backhaul capacty ncreases because the capacty dstrbuton of PDR s less far. At Mbps backhaul capacty and 00% WF-LTE coverage overlap, both WF and PDR acheve 0. and 0. respectvely n terms of farness, but ths s lower than 0. by DyBaCS... Effect of User Densty A hgh probablty that the number of users n a network wll vary drastcally from peak hour to off peak of the day exsts, especally n urban area. Furthermore, the number of users may also ncrease but gradually n resdental areas due to the growth n populaton. To evaluate how the NSSs under study cope wth the varaton of user densty, an evaluaton s carred out by varyng the number of users n the HetNet cell. A scenaro wth WF APs, a medum WF densty, s chosen and WF-LTE Coverage overlap s set to 00%. The number of users s ncreased from 00 to 0, n 0 user ncrements (Fgure ). (a) Average User Throughput (b) Farness Fgure : NSSs performance as a functon of Number of Users and Backhaul capacty. ( WF APs, 00% WF-LTE Coverage) Fgure shows that PDR provdes an advantage on average user throughput over DyBaCS when WF backhaul capacty values are low (.e. Mbps to Mbps) regardless of user densty. However, when the WF backhaul capacty s ncreased, the dfference n average user throughput between PDR and DyBaCS becomes neglgble. At hghest user densty wth 0 users per square klometer, average user throughput of DyBaCS s greater than PDR when WF backhaul capacty exceeds 0Mbps. WF remans the worst n provdng capacty to users. DyBaCS remans the best scheme n terms of farness for the entre range of user densty and backhaul capacty. Fgure mples that wth ncreasng number of users, PDR s actually losng ts advantage on average user throughput and farness to DyBaCS and WF respectvely, accentuated n Fgure whch depcts NSSs performance for all three WF node denstes consderng the hghest number of users (0 users). Fgure shows that wth 0 users, PDR s the worst n terms of farness despte prevous results (refer to Fgure and Fgure ) showng that PDR s the second best on farness. PDR s advantage on average user throughput s also slced to a thn margn when both number of users and WF node densty s hgh. For nstance, n Fgure, when number of WF nodes s, PDR s much superor n terms of average user throughput.

24 Transactons on Emergng Telecommuncatons Technologes Page of Average User Throughput (Mbps) Farness Number of WF Nodes WF PDR DyBaCS (a) Average User Throughput For Peer Revew Number of WF Nodes WF PDR DyBaCS (b) Farness Fgure : Performance comparson between NSSs as a functon of total WF Nodes wth 0 Users and fxed backhaul capacty of 0Mbps However, at hgher WF node densty, PDR s advantage on average user throughput becomes nsgnfcant. As a general concluson DyBaCS s good for farness whlst mantanng the average user throughput, a clear advantage when the number of users s hgh wth dense AP deployment, a typcal urban scenaro. It s adaptve to varyng number of WF nodes and varyng number of users, hghly relevant n fast changng envronments. PDR whch s a form of greedy algorthm maxmzes the average user throughput but at the expense of compromsed farness and ts advantages n cell throughput dmnsh when both number of users and AP densty are hgh. Although WF performs adequately compared to PDR when APs densty, user densty and backhaul capacty are hgh, t performs poorly otherwse and never outperforms DyBaCS n all scenaros under study... Performance on Non-unform Backhaul Capacty In another scenaro wth 00 users, backhaul capacty of APs coverng the entre HetNet are non-unformly assgned wth AP, AP, AP and AP equal to 0Mbps, 0.Mbps, 0Mbps and Mbps respectvely. Average user throughput s presented n Fgure a, where PDR has the hghest value (.Mbps) followed by DyBaCS (.Mbps) and WF (.Mbps). PDR s expected to offer hgher average user throughput as t selects the network based on the hghest physcal data rate wth the ntenton of maxmzng the average user throughput. However, t degrades the farness n terms of capacty dstrbuton among the users hghlghted n Fgure b where the farness ndex of PDR s only 0. compared to 0. by usng DyBaCS. Although the average throughput of DyBaCS s % lower than PDR, but the traded off seems to be worthwhle as farness s sgnfcantly mproved by %. WF only provdes a 0. farness ndex. (a) Average User Throughput (b) Farness Fgure : (a) Average user throughput and (b) Farness on bandwdth sharng wth non-unform WF backhaul capacty. ( Nodes, 00 users) (a) Average User Throughput (b) Farness Fgure : (a) Average user throughput and (b) Farness of bandwdth sharng wth non-unform WF backhaul capacty. ( Nodes, 0 users) Usng a smlar scenaro but by ncreasng the number of users to 0, Fgure b shows that farness ndex offered by PDR (at 0.) s the poorest amongst all the NSSs under study although as shown n Fgure