Radio Resource Management in Beyond 3G Systems
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- Rodger Holmes
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1 IEEE MELECON 2006, May 16-19, Benalmádena (Málaga), Spain Radio Resource Managemen in Beyond 3G Sysems Absrac.- Beyond 3G sysems is usually he erm used o refer o he new scenarios in he wireless arena where differen Radio Access Technologies (RATs) will coexis and operae in a coordinaed way. This cooperaion mus indeed be regarded as a new challenge o offer services o he users over an efficien and ubiquious radio access. In his way, he user can be served hrough he RAT ha fis beer o he erminal capabiliies and service requiremens, and also a more efficien use of he radio resources can be achieved. This challenge calls for he inroducion of new Radio Resource Managemen () algorihms operaing from a common perspecive ha ake ino accoun he overall amoun of resources offered by he available RATs. In his conex, his paper presens he framework for developing algorihms in he B3G scenarios, including some possible approaches. I. INTRODUCTION In parallel wih he developmen of he 3G cellular sysems, oher wireless access echnologies for Wireless Local Area Neworks () and Personal Area Neworks (PAN), like IEEE and Blueooh, have been developed, sandardised and have experienced a significan growh, arriving o he mass marke. In urn, in he field of cellular sysems, he exension of GSM (Global Sysem for Mobile communicaions) o GPRS (General Packe Radio Service) including packe ransmission capabiliies in he radio inerface has been a firs milesone in he evoluion pah of 2G cellular sysems owards UMTS (Universal Mobile Telecommunicaions Sysem). The co-exisence and ineracions beween UMTS and GSM/GPRS echnologies consiue one of he key poins for he success of 3G echnologies. As a maer of fac, GSM/GPRS has also followed is independen pah wih he developmen of an improved radio access echnology ha allows higher bi raes hanks o he use of more efficien modulaion schemes. The erm EDGE (Enhanced Daa raes for GSM Evoluion) is used o refer o his improved sysem and he erm GERAN (GSM/EDGE Radio Access Nework) is he name of he evolved radio access nework including hese new capabiliies. As a resul of he above, he scenarios where UMTS will be deployed will probably differ from hose for which i was iniially hough, and i will have o co-exis no only wih previous 2G and 2.5G sysems bu also wih and oher emerging echnologies. These new scenarios where differen Radio Access Technologies (RATs) will coexis and will operae in a coordinaed way are ofen referred as beyond 3G (B3G) sysems. Fig. 1 shows an example of such a heerogeneous neworks scenario. I is consiued by several radio access neworks (RAN) inerfacing a common core nework. Radio access neworks include cellular neworks, e.g. UTRAN (UMTS Terresrial Radio Access Nework) wih he wo modes FDD (Frequency Division Duplex) and TDD Ramón Agusí Universia Poliècnica de Caalunya (UPC) ramon@sc.upc.edu (Time Division Duplex), and GERAN. These neworks may in urn be subdivided ino differen cellular layers (e.g. macro, micro or picocells) depending on he expeced coverage area, and also oher public non-cellular access neworks (e.g. ). The core nework infrasrucure is ypically subdivided in he circui swiched (CS) and packe swiched (PS) domains providing access o exernal neworks, e.g. PSTN (Public Swiched Telephone Nework) or Inerne. The scenario assumes he exisence of muli-mode erminals, providing conneciviy o muliple access neworks eiher in differen ime insans or even simulaneously. Macrocell Microcell Core Nework CS domain UTRAN/FDD PSTN/ISDN Muli-mode erminal UTRAN/TDD RAT selecion PS domain GERAN (GSM/EDGE) Daa Nework (Inerne) Fig. 1 Heerogeneous neworks environmen Public Public Privae The availabiliy of several access neworks mus indeed be regarded as a new challenge o offer services o he users over an efficien and ubiquious radio access hanks o coordinaing he available RATs. In his way, no only he user can be served hrough he RAT ha fis beer o he erminal capabiliies and service requiremens, bu also a more efficien use of he available radio resources can be achieved [1]. This calls for he inroducion of new Radio Resource Managemen () algorihms operaing from a common perspecive ha ake ino accoun he overall amoun of resources available in he exising RATs, and herefore are referred o as C (Common Radio Resource Managemen) algorihms [2][3]. Furhermore, for a proper suppor of such algorihms, suiable nework archiecures and procedures mus ensure he desired inerworking capabiliies beween he differen echnologies [4]-[6]. The inerworking archiecure enhanced wih C funcionaliy will pave he way for he exension of hese heerogeneous neworks o include also new 4G radio access echnologies. This paper provides he framework for coping wih he radio resource managemen problem in beyond 3G scenarios, describing firs he differences in how he problem is deal up /06/$ IEEE 569
2 o 3G sysems and hen how he C funcionaliies are inroduced in beyond 3G sysems. Also some specific approaches o deal wih he problem are analysed. The res of he paper is organised as follows. Secion II and Secion III discuss he problem for 3G and beyond sysems, respecively. Secion IV presens he C funcional model devised in 3GPP (Third Generaion Parnership Projec) and he funcionaliies are discussed in Secion V. Finally, Secion VI presens some C soluions and he conclusions are summarised in Secion VII. II. RADIO RESOURCE M ANAGEMENT UP TO 3G SYSTEMS A Radio Resource Uni (RRU) can be defined by he se of basic physical ransmission parameers necessary o suppor a signal waveform ransporing end user informaion corresponding o a reference service. These physical ransmission parameers depend on he muliple access echnique being used. In paricular, in FDMA (Frequency Division Muliple Access), a radio resource uni is equivalen o a cerain bandwidh wihin a given carrier frequency. In TDMA (Time Division Muliple Access), a radio resource uni is equivalen o a pair of a carrier frequency and a ime slo. In CDMA (Code Division Muliple Access), a radio resource uni is defined by a carrier frequency, a code sequence and a power level. The main difference arising in CDMA is ha he required power level necessary o suppor a user connecion is no fixed bu depends on he inerference level. Thus, he amoun of ransmied power resources will vary along ime according o muliple elemens of he scenario, such as propagaion condiions, inerference, cell load level, ec. In addiion o he main physical dimensions (frequency, ime slo, code sequence and power level), here are oher physical ransmission elemens such as he modulaion scheme, channel coding scheme, ec. Clearly, depending on he exploiaion of he basic dimensions in erms of he former elemens differen specral efficiencies may follow. The objecive of a nework operaor is he deploymen of a nework able o suppor is cusomers wih he required QoS under he arge coverage area. Focusing on he radio par, he oupu of he radio nework planning will be he provision of RRUs along he service area by means of a cerain radio nework opology and a given configuraion of he cell sies. As long as e.g. service peneraion and service usage vary along ime and space, he amoun of radio resource unis o be provisioned also varies and, consequenly, he radio nework planning is an evolving process. Afer he RRUs have been provisioned in he service area during he planning phase, funcions are in charge of allocaing and managing he provisioned RRUs. Cellular mobile communicaions are dynamic in naure. Dynamism arises from muliple dimensions: propagaion, raffic generaion, inerference, ec. Thus, he dynamic nework evoluion calls for a dynamic managemen of he available RRUs, which is carried ou by means of mechanisms wih an associaed number of parameers ha need o be chosen, measured, analyzed and opimized. Besides, mechanisms may overcome a some exen he long erm reaciviy in radio nework planning and deploymen, which oherwise would preven he nework operaor o accommodae sudden and ransien raffic increases [2][7]. funcions should hen ake ino accoun he consrains imposed by he radio inerface in order o make decisions regarding he seing of he differen elemens and parameers influencing he air inerface behaviour. Some of hese are he number of acive users, he number of simulaneous users ransmiing, he corresponding ransmission raes for each user, he ransmied power levels corresponding o every simulaneous user, ec. Clearly, he number of parameers o be conrolled as well as heir differen naure claims for a se of several funcions, whose join behaviour should lead o an overall radio access nework opimisaion. The need of a conrolled air inerface usually requires a srong cenralised componen in he operaion. Neverheless, he higher signalling load associaed o a cenralised operaion usually requires having some decenralised elemens locaed in he erminal side. algorihms are fed by measuremens, some of hem provided from he erminal (e.g. serving and neighbouring cells received power levels) and some ohers from he Radio Access Nework (RAN) side (e.g. serving and neighbouring cells load level). Decisions aken from cenralised algorihms are ransferred o he erminal hrough layer 3 proocol procedures. funcions need o be consisen for boh uplink and downlink, alhough he differen naure of hese links inroduces some differences in he followed approach. Since he differen funcions will arge o rack differen radio inerface elemens and effecs, funcions can be classified according o he ime scales hey use o be acivaed and execued. Then, he se of funcions wih he corresponding ypical ime scales beween consecuive acivaions of he involved algorihm would be [2]: - Order of 1ms: Inner loop power conrol in CDMA - Order of 10ms: Packe scheduling, MAC (Medium Access Conrol) algorihms - Order of 100ms - 1s: Admission conrol, Handover, Congesion conrol, Ouer loop power conrol in CDMA funcions can be implemened in many differen algorihms, his impacing on he overall sysem efficiency and on he operaor infrasrucure cos. Addiionally, sraegies are no subjec of sandardisaion, so ha hey can be a differeniaion issue among manufacurers and operaors. The specific sraegies are leading o an increase in compeiiveness among he manufacurers. sraegies of legacy neworks (e.g. GSM/GPRS) are of raher low dimensionaliy, i.e. only a few parameers are needed o une heir opimaliy. On he conrary, in he case of UTRAN (UMTS Terresrial Radio Access Nework), he required flexibiliy o accommodae differen service requiremens ogeher wih he more sophisicaed naure of he WCDMA echnique urned ino more dimensions in he opimisaion 570
3 problem hus increasing he complexiy of he problem. Finally, s are also expeced o play an imporan role in he provision of high daa rae services, so ha should be argeed if QoS needs o be provided. III. RADIO RESOURCE MANAGEMENT IN B3G SYSTEMS In a B3G where several RATs coexis he managemen of he provisioned RRUs can be seen as a problem wih muliple dimensions. Every RAT is based on specific muliple access mechanism exploiing in urn differen orhogonal dimensions, such as frequency, ime and code. Then, local mechanisms are needed for every considered RAT: GERAN (GSM/EDGE Radio Access Nework), UTRAN and, as shown in Fig. 2 (a). In addiion o ha, a proper coordinaion among he differen RATs can be achieved wih developmen of Common (C) algorihms. C is based on he picure of a pool of radio resources, belonging o differen RATs bu commonly managed, as shown in Fig. 2 (b). Then, he addiional dimensions inroduced by he mulipliciy of RATs available provide furher flexibiliy in he way how radio resources can be managed and, consequenly, overall improvemens may follow. Noice ha he C vision allows also considering differen amouns of radio resources spaially available, because in erms of curren nework deploymen deploymen, differen spaial availabiliies are found for he exising RATs. For example, GERAN ends o be he mos widespread RAT, while UTRAN is no ye everywhere deployed and in urn hospos wih reduced coverage areas are also widespread around ciies. GERAN c UTRAN -GERAN -UTRAN - GERAN c (a) C UTRAN (b) Fig. 2 a single RAT level managing orhogonal muliple access dimensions C managing a pool of orhogonal muliple access dimensions IV. C FUNCTIONALM ODEL The funcional model assumed in 3GPP for C operaion considers he oal amoun of resources available for an operaor divided ino radio resource pools. Each radio resource pool consiss of he resource unis available in a se of cells, ypically under he conrol of a RNC (Radio Nework Conroller) in UTRAN or a BSC (Base Saion Conroller) in GERAN. Two ypes of eniies are considered for he managemen of hese radio resource pools [4][5], as shown in Fig. 3. f f - The, which carries ou he managemen of he resources in one radio resource pool of a cerain radio access nework. This funcional involves differen physical eniies in he RNS (Radio Nework Subsysem) or BSS (Base Saion Subsysem) depending on he specific considered funcions, alhough for represenaion purposes i is usual o assume he residing in he RNC or he BSC. Noice ha differen eniies do no necessarily belong o differen radio access echnologies. - The C, which is involved in he coordinaed managemen of he resource pools under differen eniies. In his way, decisions on radio resources usage may ake ino accoun he resource availabiliy in several eniies. Each C conrols a number of eniies and may communicae wih oher C eniies as well, hus collecing informaion from oher eniies ha are no under is direc conrol. - Informaion reporing - decision suppor C - Informaion reporing C - Informaion reporing - decision suppor Fig. 3 C funcional model The ineracions beween and C eniies involve mainly wo ypes of funcions: a) Informaion reporing funcion The informaion reporing funcion allows he o repor relevan informaion o is conrolling C. The reporing can be performed periodical or even-riggered, or even a a given insan, and i is oally up o C s reques. The exchange of informaion is also possible beween differen C eniies in order o know he saus of heir corresponding eniies. There are mainly wo ypes of informaion o be repored o he C : - Dynamic common measuremens on cells conrolled by a given RNC or BSC. These measuremens include he curren cell loads, ransmied carrier power, he received oal wideband power, inerference measuremens, ec. - Saic informaion on cells conrolled by a given RNC or BSC. This includes he knowledge abou he cell relaions (e.g. if hey are overlapped or if hey belong o differen HCS layers), he cell capabiliies (e.g. wheher a cell suppors GPRS, EDGE,...) he cell capaciies (e.g. he number of available ime slos) or he available QoS (e.g. maximum bi rae for a given service or average buffer delay) b) decision suppor funcion This funcion describes he way how he C and eniies inerac for aking decisions. For example, i is possible ha he C simply advises he, so ha he remains as he maser of he decisions, and, on he conrary, i is also possible ha he C is he maser so ha is decisions are binding for he. 571
4 V. C FUNCTIONS As explained in secion II, he main funcionaliies arising in he conex of a single RAN are: admission and congesion conrol, horizonal (inra-sysem) handover, packe scheduling and power conrol. When hese funcionaliies are coordinaed beween differen RANs in a heerogeneous scenario, hey can be denoed as common (i.e. hus having common admission conrol, common congesion conrol, ec.) as long as algorihms ake ino accoun informaion abou several RANs o make decisions. In urn, when a heerogeneous scenario is considered, a specific funcionaliy arises, namely RAT selecion (i.e. he funcionaliy devoed o decide o which RAT a given service reques should be allocaed). Afer he iniial RAT selecion decision, aken a session iniiaion, verical (iner-sysem) handover is he procedure ha allows swiching from one RAN o anoher. The successful execuion of a seamless and fas verical handover is essenial for hiding o he user he underlying enabling infrasrucure. Issues relaed o verical handover comprise scanning procedures for he erminal o discover available RANs, measuremen mechanisms o capure he saus of he air inerface in he differen RANs, verical handover riggers (i.e. he evens occurring in he heerogeneous nework scenario ha require he sysem o consider wheher a verical handover is acually required or no), verical handover algorihm (i.e. he crieria used o decide wheher a verical handover is o be performed or no) and proocol and archiecural aspecs o suppor handover execuion. Verical handover procedures from one RAN o anoher may be useful o suppor a variey of objecives, such as avoiding disconnecions due o lack of coverage in he curren RAT, blocking due o overload in he curren RAN, possible improvemen of QoS by changing he RAT, suppor of user s and operaor s preferences in erms of RANs usage or load balancing among RATs. Thus, he verical handover procedure enables anoher dimension ino he C problem and provides an addiional degree of freedom in rearranging raffic [3][8]-[10]. VI. C SOLUTIONS According o he framework presened in he previous secions in he following some specific soluions are addressed coping wih he RAT selecion problem in heerogeneous scenarios. A. Policy-based RAT selecion schemes in UTRAN/GERAN Policy-based managemen has been he subjec of exensive research during he las years in IP-based muliservice neworks [11], and may also be considered as a possibiliy for C design. A policy can be defined as a high-level declaraive direcive ha specifies some crierion o guide he behaviour of a nework responding o some nework operaor preferences. In he following several policies for RAT selecion in a heerogeneous scenario including UTRAN and GERAN are discussed. a) Service Based RAT selecion A service-based RAT selecion policy is based on a direc mapping beween services and RATs [12]. As an example, in a scenario including voice and ineracive service assuming all erminals have muli-mode capabiliies (i.e. hey can work eiher wih UTRAN or GERAN), wo possibiliies would be: - VG (voice GERAN) policy: This policy allocaes voice users ino GERAN and ineracive services ino UTRAN. - VU (voice UTRAN) policy: This policy allocaes voice users ino UTRAN and ineracive services ino GERAN. If no capaciy is available in he primary RAT, he oher RAT is seleced insead. If no capaciy is available in he alernaive RAT, he service reques ges blocked (a service se-up) or dropped (during service life-ime). Table I compares he performance in erms of aggregaed hroughpu (i.e. including boh voice and www users) when basic policies VU and VG are considered in a scenario wih seven omnidirecional cells wih radius 1 km for UTRAN and GERAN assuming ha he cells of boh sysems are co-sied. Noice ha, in all he cases, VG policy ouperforms VU, revealing he suiabiliy of allocaing voice users in GERAN. The main reasons are wo-fold. Firs, wih respec o www users, a higher hroughpu can be obained in UTRAN as long as DCH channels are used while in GERAN www users are subjec o a scheduling algorihm. In urn, from he voice users poin of view, if he disance beween cell radius was se o 500m, no significan differences would be observed beween VU and VG (he resuls are no shown for he sake of breviy), bu when increasing he radius, a higher degradaion is observed in VU because UTRAN users a he cell edge experience some erroneous ransmissions due o power limiaions and he inerference-limied naure of WCDMA. TABLE I TOTAL THROUGHPUT (MB/S) FOR TWO POLICIES Users VU VG Voice www UL DL UL DL b) Load Balancing-based RAT selecion Load balancing (LB) is anoher possible guiding principle for resource allocaion in which he RAT selecion policy will disribue he load among all resources as evenly as possible. Specifically, he seleced RAT will be he one having he lowes load. Therefore, an influenial run-ime parameer in a load balancing decision-making procedure is he load meric. For UTRAN, an average of he cell load facor can be used, while in GERAN a useful way o measure he daa load is o measure he average amoun of ime slos uilized by GSM/EDGE services. Fig. 4 compares he LB RAT selecion algorihm agains he service-based VG policy in a scenario wih seven omnidirecional cells for UTRAN and GERAN co-sied wih cell radius 500m. Paricularly, i shows he voice call dropping probabiliies (in %) for boh algorihms. Up o 600 voice users, dropping values are kep sufficienly low. For 800 voice users however, VG reveals higher dropping values han policy LB. The higher dropping raes experienced by VG policy is 572
5 explained bearing in mind he load disribuion in GERAN induced by VG and LB policies. In paricular, for VG he load is a is maximum value mos of he ime which implies a lack of flexibiliy in order o accommodae handover users being redireced o GERAN. Therefore, VG may incur in more poenial dropping siuaions han in he case of LB policy appliance which presens more flucuaions in he load values and can provide resources o incoming handover users if necessary. Dropping voice (%) ineracive voice users VGVU LB Fig. 4 Dropping Probabiliy (%) considering VG and LB policies. c) Radio Nework based RAT selecion This caegory of policies for he RAT selecion procedure akes ino accoun he differen resource consumpion ha a given user may have in one or oher RAT depending on he specific nework characerisics. As an example, le consider in he following he so-called IN (indoor) policy. In his case he selecion would be done aking ino accoun wheher a user is locaed indoor or oudoor, under he consideraion ha WCDMA capaciy is highly degraded by indoor raffic users, as saed in [13], where capaciy reducions of up o 80% are observed when half of he users in a scenario are indoor. Consequenly, according o his policy indoor users will be allocaed in GERAN while oudoor users will be allocaed in UTRAN. I is worh menioning ha oher similar policies could also be considered making use of e.g. pah loss measuremens (i.e. allocaing high pah loss users in GERAN and low pah loss users in UTRAN). UL BLER UTRAN (%) RN policy IN policy Voice users Fig. 5. UL BLER in UTRAN for wo basic policies. Fig. 5 plos he uplink block error rae (BLER) in UTRAN in a a scenario where 30% of he users are indoor and he cell radius is 500m. In order o see clearly he effecs of he IN policy only voice raffic is considered, and he IN policy is compared wih a reference random policy (RN) in which users are allocaed randomly wih equal probabiliy in GERAN and in UTRAN. I can be observed ha, when he IN policy is applied, he BLER is significanly reduced. B. Fuzzy-Neural based C in UTRAN/GERAN/ From he above soluions shown in he previous secion i has been observed ha he C operaion can be guided by very differen principles, relaed wih echnical aspecs as well as wih operaor policies. Furhermore, one of he problems ha C algorihms mus face is he exisence of uncerainies when comparing differen measuremens belonging o differen RATs ha are necessarily of a differen naure ogeher wih subjecive crieria ha have o do wih echnoeconomic issues. As a resul, he use of fuzzy logic as a robus decision making procedure becomes anoher possible soluion for C algorihm developmen. The fuzzy subse mehodology has been proved o be good a explaining how o reach he decisions from imprecise informaion by using he fuzzifier and defuzzifier rules and he inference engine concep [14][15]. On he oher side, he use of neural neworks, which are good in recognizing paerns by means of learning procedures, could also be considered and, as a maer of fac, hey have been proposed o be used in hybrid fuzzyneural based sysems [16][17]. Taking hese consideraions ino accoun, in he following he characerisics of a fuzzy neural C soluion are dis cussed in a scenario wih UTRAN, GERAN and access echnologies. Fig. 6 depics he block diagram of he Fuzzy-Neural C. Two main blocks are idenified, named fuzzy neural and reinforcemen learning. In addiion o hem, oher blocks including echno-economical aspecs could also be included [18]. A brief descripion of hese blocks is deailed in he following. For deails he reader is referred o [18][19]. LV 1 LV N FUZZIFIER FUZZY NEURAL REINFORCEMENT LEARNING INFERENCE ENGINE DEFUZZIFIER Fig. 6 Block diagram of he Fuzzy-Neural C algorihm Allocaed BW RAT seleced The purpose of he fuzzy neural algorihm is o obain for each RAT a numerical indicaion (denoed as Fuzzy Seleced Decision: FSD) beween 0 and 1 of he suiabiliy o selec i. The decision is obained from a se of inpu linguisic variables (LVi), reflecing echnical measuremens. This decision is aken in hree seps, as depiced in Fig. 6. Sep 1.- Fuzzificaion. This process assigns, for each inpu linguisic variable, a value beween 0 and 1 corresponding o he degree of membership of his inpu o a given fuzzy subse. A fuzzy subse is a linguisic subjecive represenaion of he inpu variable. The considered inpu variables are he signal srengh (SS) and he resource availabiliy (RA) for each of he considered RATs and he mobile speed. Jus as an example, a fuzzy subse for he resource availabiliy RA (e.g. for he number of available ime slos in GERAN) could be formed by he possibiliies H (high), M (medium) and L (low). There exiss one membership funcion for each one of he hree erms 573
6 H, M and L, reflecing he degree of membership of he RA value o each erm. Sep 2.- Inference Engine. For each combinaion of fuzzy subses from sep 1, he inference engine makes use of predefined fuzzy rules o indicae, for each RAT, he suiabiliy of selecing i. So, a he oupu of his sep here will be a combinaion of hree oupu linguisic variables D (D UTRAN, D GERAN, D ) each one wih four fuzzy subses: Y(yes), PY (probably yes), PN (probably no) and N (no), wih differen degrees of membership for each of hem. Togeher wih he suiabiliy of selecing each RAT, he inference engine can also deermine a level of allocaed bandwidh in i wih he fuzzy subses H (high), M (medium) and L (low). Sep 3.- Defuzzificaion. This procedure convers he oupus of he inference engine ino a number ranging beween 0 and 1, named Fuzzy Seleced Decision (FSD) for each RAT ha reflecs he suiabiliy of selec i. The seleced one will be hen he one having he highes FSD. This procedure also provides he allocaed bandwidh in he seleced RAT. The reinforcemen learning procedure is used o suiably une he parameers of he differen and raher subjecive funcions involved in he fuzzy logic conroller [16] in order o ensure a cerain arge value of a QoS parameer, like e.g. he raio of non-saisfied users (i.e. he users ha receive a bandwidh below a cerain desired value), he raio of blocked users, dropping calls, ec. An example of he performance ha can be obained by means of he fuzzy-neural C sraegy operaing wih reinforcemen learning is shown in Fig. 7. I presens he ime evoluion of he percenage of non-saisfied users in a simple scenario wih hree concenric cells: one UTRAN cell, one GERAN cell and one access poin. In his example he simulaion ime is measured in periods of 100 ms. Two values of he arge raio of non-saisfied users are considered, namely P*=1% and P*=3% and i can be noiced ha he algorihm is able o converge o he desired value under variable raffic and mobiliy condiions. Non-saisfied Users (%) P*=3 P*= Simulaion Time Fig. 7 Evoluion of he probabiliy of non saisfied users VI. CONCLUSIONS This paper has focused on he problem in heerogeneous wireless neworks where differen RATs coexis. The framework for developing C sraegies including he funcional model and a descripion of he major funcionaliies has been provided. Also differen approaches for he RAT selecion procedure have been presened, making use of policy-based sraegies and fuzzy-neural mehodology. REFERENCES [1] G.Fodor, A. Eriksson, A. Tuoriniemi, Providing Qualiy of Service in Always Bes Conneced Neworks, IEEE Communicaions Magazine, July, 2003, pp [2] J. Pérez-Romero, O.Sallen, R.Agusí, M. Díaz-Guerra, Radio Resource Managemen Sraegies in UMTS, John Wiley & Sons, [3] A. Tölli, P. Hakalin, H. Holma, Performance Evaluaion of Common Radio Resource Managemen (C), ICC Conference, Vol. 5, April, 2002, pp [4] 3GPP TR v5.0.0 Improvemen of across RNS and RNS/BSS [5] 3GPP TR v0.3.0 Improvemen of across RNS and RNS/BSS (Pos Rel-5) (Release 6) [6] J. Pérez-Romero e al. Common Radio Resource Managemen: Funcional Models and Implemenaion Requiremens, 16h PIMRC Conference, Berlin, [7] J. Zander, S.-L. Kim, Radio Resource Managemen for Wireless Neworks, Arech House, [8] S. Lincke-Salecker, The Benefis of Load Sharing when Dimensioning Neworks, Proceedings of he 37 h Annual Simulaion Symposium (ANSS 04), April, [9] S. Lincke-Salecker, Performance and Service Issues in Selecing Adapive Placemen as a Load Disribuion Technique, IEEE 59h Vehicular Technology Conference, VTC 2004-Spring, Milan, [10] M. Sieber, M. Schinnenburg, M. Lo, Enhanced Measuremen Procedure for Verical Handover in Heerogeneous Wireless Sysems, 14h PIMRC Conference, Beijing, [11] P. Flegkas, P. Triminzios, G. Pavlou, A Policy-Based Qualiy of Service Managemen Sysem for IP DiffServ Neworks, IEEE Nework, March-April, 2002, pp [12] J. Pérez-Romero, O. Sallen, R. Agusí Policy-based Iniial RAT Selecion algorihms in Heerogeneous Neworks, 7h MWCN Conference, Marrakesh, [13] J. Pérez-Romero, O. Sallen, R. Agusí, On The Capaciy Degradaion in W-CDMA Uplink/Downlink Due o Indoor Traffic, VTC in Fall 04 conference, Los Angeles, USA, [14] J.M. Mendel, Fuzzy Logic Sysems for Engineering: A Tuorial, Proceedings of he IEEE, Vol. 83, No.3, March, 1995, pp [15] R.R. Yager, Muliple Objecive Decision Making using Fuzzy Ses, In l Man-Machine Sudies, No. 9, 1977, pp [16] C.T. Lin, C.S. George Lee Neural-Nework-Based Fuzzy Logic Conrol and Decision Sysem, IEEE Transacions on Compuers, Vol. 40, No.12, December 1991, pp [17] K R Lo, C. B. Shung, A Neural Fuzzy Resource Manager for Hierarchical Cellular Sysems Supporing Mulimedia Services, IEEE Transacions on Vehicular Technology, Vol. 52, No. 5, Sepember 2003, pp [18] R. Agusi, O. Sallen, J. Pérez-Romero, L. Giupponi A Fuzzy- Neural Based Approach for Join Radio Resource Managemen in a Beyond 3G Framework, Firs Inernaional Conference on Qualiy of Service in Heerogeneous Wired/Wireless Neworks, Qshine 04, Dallas, USA, Ocober, [19] L. Giupponi, R. Agusi, J. Pérez-Romero, O. Sallen, Join Radio Resource Managemen algorihm for Muli-RAT neworks, IEEE Globecom, San Luis, USA, November,
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