7h WSEAS Inernaional Conference on Applicaion of Elecrical Engineering (AEE 08), Trondheim, Norway, July 2-4, 2008 Muli-Objecive Nework Design and Opimizaion for Wireless Local Area Neworks CHUTIMA PROMMAK Deparmen of Telecommunicaion Engineering, Suranaree Universiy of Technology 111 Universiy Road, Muang Disric, Nakhon Rachasima, 30000 THAILAND Absrac: - This paper presens a muli-objecive wireless local area neworks design and opimizaion. The proposed model combines hree problems ogeher, including he opimal access poin placemen, he frequency channel assignmen and he power level assignmen. In addiion, i accouns for user populaion densiy in he service area, raffic demand characerisics and he physical srucure of he service area. The design model aims o deermine a nework configuraion ha opimizes he nework qualiy of services in erm of he radio signal coverage and he daa rae capaciy o serve expeced user raffic demand in he service area. Numerical resuls and sensiiviy analysis is performed o analyze he nework qualiy of service. Key-Words: - Muli-objecive, Opimizaion, Nework design, Wireless Local Area Neworks 1 Inroducion Wih he coninued growh and he expansion of he infrasrucure-based Wireless Local Area Nework (WLAN) deploymens, efficien nework design mehods are required so ha he resuling WLANs can provide high Qualiy of Services (QoS). An infrasrucure nework employs an access poin (AP) for cenral conrol of he communicaion beween wireless users paricipaing in a Basic Service Se (BSS). A coverage area wihin which wireless users are free o move around and ye sill remain conneced o he AP is called a Basic Service Area (BSA) which covers an area ranging from 20 o 300 meers in radius depending on he ransmiing power level and he radio propagaion environmens [1]. For large service regions, a cellular archiecure wih muliple BSAs can be used in which he APs are inerconneced via a wired disribuion infrasrucure o form a single sysem called an Exended Service Se (ESS). Fig.1 illusraes an ESS where hree BSAs exis. Noe ha some of BSAs in he ESS can overlap. In his paper, we aim o solve he problem of laying ou BSAs o cover a arge region and achieve high qualiy of services. In paricular, we aim o deermine he opimal nework configuraion (i.e. he locaion, frequency channel and power level of each AP) in order o maximize he nework qualiy of services in erm of he radio signal coverage and he daa rae capaciy o serve expeced user raffic demand in he service area. The issue on he qualiy of signal in he arge service areas and he concerns abou he user daa rae capaciy are wo imporan merics o be accouned in deermining he opimal nework configuraion. However, he majoriy of he published papers do no seek all hree parameers of he nework configuraion and he aenion is focused on eiher one of he design aspecs. Tradiional works focus on he AP placemen problems. The design focus mainly on he signal qualiy aspec, aiming o maximize Signal o Noise Raio (SNR) [2] or minimize pah loss [3,4]. Oher works [5,6] consider he frequency channel assignmen problems for WLANs. Ref [5] aims a maximizing he oal received signal srengh whereas Ref. [6] aims a maximizing he coverage availabiliy. Ref. [7] considers boh he AP placemen and he frequency assignmen problems by maximizing daa rae capaciy of he nework bu no considering he signal coverage aspec. In his paper we propose a muli-objecive WLAN design approach, opimizing boh he signal qualiy and he daa rae capaciy aspec o solve he AP placemen, frequency channel and power level assignmen problem. Moreover, he proposed model ESS BSA 1 AP1 W1 BSA 3 W4 AP3 W2 W5 W3 AP2 BSA 2 Fig.1 Infrasrucure-based WLANs ESS = Exended Service Se AP = Access Poin W = Wireless user Basic Service Area (BSA) Communicaion link ISBN: 978-960-6766-80-0 21 ISSN 1790-5117
7h WSEAS Inernaional Conference on Applicaion of Elecrical Engineering (AEE 08), Trondheim, Norway, July 2-4, 2008 accouns for user populaion densiy in he service area, raffic demand characerisics and he physical srucure of he service area. The res of he paper is organized as follows. The nex secion describes he problem definiion of he WLAN design model and gives he mahemaical formulaion of he design model. Secion 3 gives numerical resuls and discussion. Secion 4 provides conclusions. 2 Problem Definiion and Formulaion We propose a problem formulaion for WLAN configuraion design seeking he opimal locaion, frequency channel and power level of each AP in a service area, in order o opimize he nework qualiy objecives described below. 2.1 Nework Qualiy Objecives 2.1.1 Radio Signal Coverage Objecive We consider signal qualiy in he proposed nework design model because he service availabiliy of he nework depends on availabiliy of he radio signal and he level of inerferences in he area. To achieve a paricular daa ransmission rae, wireless users mus be wihin a cerain range of he received signal srengh and he SIR hreshold. Thus, an imporan design objecive is o maximize he signal coverage availabiliy. We evaluae he signal coverage availabiliy by defining Signal-Tes-Poins (STP) where he received signal srengh and he SIR are assessed. To maximize he signal coverage availabiliy is o maximize he number of STPs of which he received signal srengh and he SIR level are greaer han he specified hreshold. 2.1.2 Daa Rae Capaciy Objecive As he user populaion grows and mulimedia applicaions requiring higher daa rae spread, he obainable user daa rae (hroughpu of each wireless users) becomes an essenial concern in designing WLANs [1]. According o capaciy analysis of he CSMA/CA proocol used in WLANs, he average user obainable daa rae can vary depending on he number of acive wireless users on he AP. As he number of wireless users wih acive daa ransfer connecions o a paricular AP increases, he effecive AP capaciy decreases. Thus, he locaion of APs should be a funcion of he densiy characerisics of he wireless users as well. Nework race sudies [8-10] repor ha average obainable user daa raes does no depend merely on he number of wireless users exising in he service area, bu also on he aciviy of users. Addiionally, raffic volume in he nework correlaes wih user behavior [8]. User behavior in urn correlaes o he ypes of locaions where users are siuaed and he major aciviies users ypically pursue in hose locaions [8-10]. We incorporae informaion abou characerisics of WLAN usage and raffic paerns ino he design model by using he demand node concep [11]. A user aciviy level α parameer accouns for he correlaion beween nework usage characerisics and user locaions. α is he percenage of wireless users in a sub-area of ype who are simulaneously acive in daa ransfer hrough APs. Acive users paricipae in medium conenion o gain access o a communicaion channel and share AP capaciy. We define hree ypes of sub-areas: T = {1, 2, 3} where 1 denoes privae sub-areas, such as offices, 2 denoes public sub-areas for unscheduled aciviies, such as suden lounges, and 3 denoes public subareas for schedule-based aciviies, such as classrooms. The remaining user (1 α ) are idle users who, alhough siuaed in a sub-area of ype, do no generae daa ransfer aciviy over he nework a a paricular ime and herefore do no affec AP capaciy [10]. An average user daa rae requiremen in sub-area of ype (R ) imposes a desired link rae ha should be available o acive users in average. 2.2 Muli-Objecive Problem Formulaion The WLAN configuraion design problem is formulaed as a Muli-Objecive Problem (MOP), which combines wo measures of nework service qualiies: radio signal coverage and daa rae capaciy. MOP seeks an opimal nework configuraion, i.e. he opimal locaion, frequency channel and power level of each AP in a service area. Le A denoes a se of APs used in he service area, where n is he oal number of APs required. Le Ω j = {p j, f j,(x j, y j, z j )} denoe a se of decision variables which are parameers assigned o ap j for j = 1, 2,, n. p j denoes he power level assigned o ap j. f j denoes he frequency channel assigned o ap j, and (x j, y j, z j ) denoes he coordinae (x j, y j ) on floor z j where ap j is locaed. Le G denoes a se of signal es poins (STPs) represening locaions for esing he received signal srengh and he SIR level. Each STP g h refers o a coordinae in hree-dimensional space (x h, y h, z h ), where z h is he floor where g h is locaed. Le U denoes a se of demand nodes where index indicaes he ype of sub-area where demand node i is locaed. U U is a se of demand nodes in sub-area ype. The posiion of demand node i wihin he service area is denoed by (x i, y i, z i ), ISBN: 978-960-6766-80-0 22 ISSN 1790-5117
7h WSEAS Inernaional Conference on Applicaion of Elecrical Engineering (AEE 08), Trondheim, Norway, July 2-4, 2008 where (x i, y i ) is he coordinaes on floor z i where he demand node i is locaed. The user aciviy level (α ) and he average daa rae requiremen (R ) specify he nework usage characerisics of he demand node. The se of demand nodes ogeher wih he sub-area classificaion and parameers specifying nework usage characerisics (α and R ) are given as inpu o he design process. Oher decision variables include u and g. u is a user associaion binary variable ha equals 1 if demand node i U associaes o ap j A; 0 oherwise. g is a signal availabiliy binary variable ha equals 1 if STP h G can receive a signal from ap j A; 0 oherwise. Le P is he se of candidae power levels (discree values) for variable p j. F is he se of candidae frequency channels for variable f j and O is he se of candidae locaions for AP placemen. Parameers in he design process are classified ino saic and dynamic parameers. Saic parameers do no change during he design process because hey depend solely on sandard requiremens and he characerisics of user aciviy in service area. Saic parameers specifying he physical signal requiremens (e.g., he received signal srengh (P Rhreshold ) and he SIR level (SIR hreshold )), user profiles (e.g., he user aciviy level (α ) and he average user daa rae requiremen (R )), and he daa rae capaciy of AP (C). Dynamic parameers are recompued each ime a variable changes value during he design process. Dynamic variables include received signal srengh ( ), inerference level ( Inf ), and average obainable daa rae ( r i ). The mahemaical model of MOP for he WLAN design is wrien as follows: Objecives: 1) Maximize signal coverage area Maximize g h G j A P R f1 = (1) G f 1 measures he signal coverage availabiliy. I is he normalized number of STPs which he received signal srengh and he SIR level are greaer han he specified hreshold. 2) Maximize user saisfacion β u T j A i U Maximize f = (2) 2 β U ( ) T f 2 measures he user saisfacion level. I is he normalized number of users ha can obain he required daa rae. β is a relaive imporan weigh of user ype. I is defined as he raio of he required daa rae of user ype o he maximum bi rae capaciy of he AP, β = C. Consrains: j A u u R / u 1, i U (3) ( P R P Rhreshold ) 0 ( P Inf SIR ) 0 R i U, j A ( r R ) 0 hreshold, i U, j A (4), (5) u i, i U, j A (6) g g ( P R P Rhreshold ) 0 ( P Inf SIR ) 0 R h G, j A hreshold, h G, j A (7), (8) u { 0,1}, i U, j A (9) g { 0,1}, h G, j A (10) Consrain (3) specifies ha each user can associae o a mos one AP. The decision variable u can be equal o one if he received signal srengh ha user i received from he ap j (P R in dbm) and he SIR level wih respec o he ap j (he received signal srengh ( in dbm) less he inerference level (Inf in dbm)) mee he receiver sensiiviy hreshold (P Rhreshold ) and he SIR hreshold (SIR hreshold ) as specified by consrain (4) and (5), respecively. In addiion, when u is equal o one, consrain (6) mus be saisfied. I ensures ha he average daa rae available o wireless user i which is a ype user ( ) is greaer han he specified user daa rae (R). The 802.11 capaciy model and he user aciviy paern correlaed wih he ype of sub-areas where users locae are incorporaed in his consrain o esimae he average daa rae ha he acive wireless user can obain [12]. u is equal o zero oherwise. Consrains (7) and (8) assess he radio signal qualiy a he STP h, esing he received signal r i P R ISBN: 978-960-6766-80-0 23 ISSN 1790-5117
7h WSEAS Inernaional Conference on Applicaion of Elecrical Engineering (AEE 08), Trondheim, Norway, July 2-4, 2008 srengh and he SIR level. The decision variable g can be equal o one if he received signal srengh a he STP h ransmied from he ap j ( ) and he SIR level wih respec o he apj (i.e., P R PR Inf mee he received sensiiviy hreshold (P Rhreshold ) and he SIR hreshold (SIR hreshold ). Oherwise, g is equal o zero. Consrains (9) and (10) specify ha variable u and g are binary {0, 1} variables, respecively. 3 Numerical Resuls Numerical experimens were conduced on he service area in he building wih four floors. The building comprised of classrooms, offices, laboraories, suden lounges, and a library. The dimension of each floor is 33m 21m. The service area is divided ino grids of size 1m 1m. The grid poins specify he STPs. In fig.5-8, he symbol represens he demand nodes locaed in public areas for scheduled aciviies, he symbol represens he demand nodes locaed in public areas for unscheduled aciviies, and he symbol represens he demand nodes locaed in privae areas. User aciviy levels corresponding o each sub-area ype are based on sudies showing ha users in privae sub-areas are he mos acive nework users, followed by users in he public areas for unscheduled aciviies and hen users of public areas for schedule-based aciviies [8-10]. Similarly, he average user daa raes are aken from observed nework usage characerisics [8-10]. Table 1 summarizes he nework usage characerisics. Table 2 summarizes he inpu parameers of he nework design problem. The design aims for 95% coverage availabiliy a he edge of AP coverage areas. In his case, a fading margin of 5.75 db is applied in he signal coverage calculaion. We applied he proposed MOP o he WLAN configuraion design for he four-sory building. A scalarizing funcion (11) (a weighed sum of he objecives) is applied o conver a muli-objecive problem o a single objecive problem. Max F = w 1 f 1 + w 2 f 2 (11) The paching algorihm [7] is applied o solve he scalarizing funcion. The maximum poin found is a paricular poin on he Pareo fron. For example, in fig.2, F i is a scalarizing funcion when using a weigh se i (w 1i, w 2i ). F * i is a single poin on a feasible region boundary where he line defined by he weighed sum F i is angen. F * i is a paricular poin on he Pareo fron ha is he maximum of F i. ) Sensiiviy analysis is conduced o sudy effecs of weigh facors on he WLAN qualiy of service in erm of he signal coverage availabiliy and he user saisfacion level. In paricular, we generae an approximaed Pareo fron by running he program many imes using differen weigh ses. Each weigh se converges o differen maximum poin on he Pareo fron. The resuls ploed in Fig. 3 demonsrae his behavior. The ploed is obained by running he paching algorihm o solve he nework design opimizaion five imes, using five differen weigh ses (Q = 5) in which he weigh values are spread equally as wrien in Eq. (12). We use seven APs in his experimen. The poins in Fig. 3 are he maximum poins found wih each se of weighs. Two end of he fron are a (f 1 =34%, f 2 =67.6%) and (f 1 =75.4%, f 2 =58%). w 1q = (q-1)/(q-1), w 2q = 1- w 1q (12) where q = 1, 2,, Q, Q = he number of differen weigh ses In fig.3, We can observe ha as he w 2q increases from 0 o 1, he user saisfacion level increases abou 40% while he signal coverage availabiliy decreases abou 10%. We can see ha when we incorporae he issue of he daa rae capaciy in he design model, we can grealy improve he qualiy of service in erm of daa rae requiremen while slighly degrading he signal coverage availabiliy. We conduc anoher se of experimens using differen values of Q o observe he disribuion of he Pareo fron. Fig. 4 presens he resuls obained by using seven values of Q (Q = 4, 5,, 10) o generae weigh ses. The poins found wih a se of weighs generaed by each Q are depiced wih a differen shape. I can be observed ha he poins spread ou more oward he middle and he lower righ corner of he fron. The upper lef corner of he fron is around (f 1 =67.6%, f 2 =34%) where he weigh f 1 * F 1 Pareo fron Feasible region F i * F i = w 1i f 1 + w 2i f 2 Fig.2 Weighed sum of he objecives and he pareo fron F n * f 2 ISBN: 978-960-6766-80-0 24 ISSN 1790-5117
7h WSEAS Inernaional Conference on Applicaion of Elecrical Engineering (AEE 08), Trondheim, Norway, July 2-4, 2008 se is (w 1q =1, w 2q =0). We can draw a similar observaion ha slighly increasing value of w 2q can improve he user saisfacion level grealy while slighly degrading he signal coverage availabiliy. For example, a he weigh se of (w 1q =0.87, w 2q =0.13), he user saisfacion level increases 22% whereas he signal coverage availabiliy reduces 3.6% (i.e., f 1 =64%, f 2 =56%). 4 Conclusion This paper presens a novel mahemaical model for a WLAN configuraion design which is formulaed as a Muli-Objecive Problem ha combines wo measures of nework service qualiies: radio signal coverage and daa rae capaciy. A scalarizing funcion is applied o conver a muli-objecive problem o a single objecive problem. Sensiiviy analysis is conduced o sudy effecs of weigh facors on he WLAN qualiy of service in erm of he signal coverage availabiliy and he user saisfacion level. From numerical resuls we can conclude ha incorporaing he issue of he daa rae capaciy in he design model can grealy improve he qualiy of service in erm of daa rae requiremen while slighly degrading he signal coverage availabiliy. Acknowledgmen: This work was suppored by he Thailand Research Fund (Gran number MRG5080381). References: [1] A. Hills, "Large-scale wireless LAN design," IEEE Communicaion Magazine, vol. 39, pp. 98-104, 2001. [2] E. Tangpraser and N. Waanapongsakorn, Muli- Objecive Design and Opimizaion of Oudoor Wireless Lan Sysem, The 21 s Inernaional Technical Conference on Circuis/Sysems, Compuers and Communicaions, 2006 pp. 625-628 % Signal coverage 70 68 66 64 62 60 58 56 54 52 50 30 40 50 60 70 80 % User saisfacion Fig.3 Resuls wih differen weigh ses (Q=5) Q=5 [3] S. Kouhbor, J. Ugon, A. Kruger, and A. Ruginov, Opimal Placemen of Access Poin in WLAN Based on a New Algorihm, The Inernaional Conference on Mobile Business, 2005. [4] M. Unbehaun and J. Zander, Infrasrucure Densiy and Frequency Reuse for User-Deployed Wireless LAN Sysems a 17 GHz in an office environmen, IEEE Inernaional Conference on Communicaions, 2001 pp. 2535-2539. [5] R. C. Rodrigues, G. R. Maeus, and A. A. F. Loureiro, On he Design and Capaciy Planning of a Wireless Local Area Nework, IEEE Conference on Nework Operaions and Managemen Symposium, 2000 pp. 335-348. [6] C. Prommak and B. Deeka, On he Analysis of he Opimal Frequency Planning for Wireless Local Area Neworks, The Fourh PSU Engineering Conf. (PEC-4), pp. 77-81, December 2005 [7] X. Ling and K. Lawrence Yeung Join Access Poin Placemen and Channel Assignmen for 802.11 Wireless LANs, IEEE Wireless Communicaions and Neworking Conf., pp. 1583-1588, 2005. [8] M. Balazinska and P. Casro, "Characerizing mobiliy and nework usage in a corporae wireless local-area nework," Inernaional Conference on Mobile Sysems, Applicaions, and Services (MobiSys'03), San Francisco, CA, USA, May 2003. [9] D. Koz and K. Essien, "Characerizing usage of a campus-wide wireless nework," Deparmen of Compuer Science, Darmoun College Technical Repor TR2002-423, March 2002. [10] A. Balachandran, G. M. Voelker, P. Bahl, and P. V. Rangan, "Characerizing user behavior and nework performance in a public wireless LAN," ACM SIGMETRICS'02, June 2002. [11] K. Tuschku, "Demand-based radio nework planning of cellular mobile communicaion sysems," INFOCOM 98, vol. 3, pp. 1054-1061, 1998. [12] M. Heusse, F. Rousseau, G. Berger-Sabbael, and A. Duda, "Performance Anomaly of 802.11b," INFOCOM, April 2003. % Signal coverage 70 68 66 64 62 60 58 56 54 52 50 Q=10 Q=9 Q=8 Q=7 Q=6 Q=5 Q=4 30 40 50 60 70 80 % User saisfacion Fig.4 Resuls wih differen weigh ses (Q=4,5,,10) ISBN: 978-960-6766-80-0 25 ISSN 1790-5117
7h WSEAS Inernaional Conference on Applicaion of Elecrical Engineering (AEE 08), Trondheim, Norway, July 2-4, 2008 Table 1 Nework usage characerisics Sub-areas User aciviy level Average user daa rae (Kbps) Type 1: Privae sub-areas α 1 = 0.50 R 1 = 460 Type 2: Public sub-areas for unscheduled aciviies α 2 = 0.40 R 2 = 260 Type 3: Public sub-areas for schedule-based aciviies α 3 = 0.35 R 3 = 80 Table 2 Nework parameers used in he muli-objecive opimizaion for WLAN design Parameer Definiion Value Candidae se for Variables: P Se of candidae power levels for variable p j {0, 7, 13, 15, 17, 20, 24} in dbm F Se of candidae frequency channels for variable f j {2.412, 2.437, 2.462} in GHz Saic Parameers: α User acive level R Average user daa rae requiremen in sub-area ype See Table 1 P Rhreshold Received sensiiviy hreshold -80 dbm SIR hreshold Signal o inerference raio hreshold 10 db C Daa rae capaciy of he ap j for j A 11 Kbps Pah loss Parameers: d 0 Reference disance d 0 1 meer n Pah loss exponen 3.3 δ Sandard deviaion represening shadow fading 3.5 db Anenna Parameers: G AZ Anenna gain (peak direciviy) 2.5 db Fig.5 Service area (he 1 s firs floor) Fig.6 Service area (he 2 nd second floor) Fig.7 Service area (he 3 rd hird floor) Fig.8 Service area (he 4 h forh floor) ISBN: 978-960-6766-80-0 26 ISSN 1790-5117