An Admission Control Framework Integrating Radio and IP-Transport in 3GPP-based Networks

Transcription

1 An Admsson Framework Integratng Rado and IP-Transport n 3GPP-based Networks R. Ferrús, J. Olmos, O. Sallent, J. Pérez-Romero, F. Casadevall Sgnal Theory and Communcatons Department, UPC, Barcelona e-mal: [ferrus, olmos, sallent, jorperez,ferranc]@tsc.upc.edu Abstract- Wthn the context of Beyond 3G (B3G) wreless networks, there s a clear mgraton towards the usage of IP/MPLS transport networks wthn the backhaul part of the rado access network (RAN). Despte expected cost savngs and ease of mantenance, such a mgraton mposes new challenges on the IP QoS provsonng. These new challenges are fuelled by, on one hand, the traffc ncrease n the RAN due to the more effcent ar nterfaces, and on the other hand, potental bandwdth lmtatons lkely to exst n typcal backhaul network deployments. Ths paper develops a call admsson control (CAC) framework that consders both the rado nterface and also the IP transport network. Ths leads to a new paradgm where transport resources are consdered not only at the network dmensonng stage but are ncluded n an ntegrated resource management scheme. The CAC framework s valdated by analysng a specfc CAC algorthm n the context of UTRAN wth IP-based transport. I. INTRODUCTION It s wdely recognzed that B3G networks wll mgrate to all-ip archtectures n the medum-term. Ths mgraton to all-ip archtectures has dfferent components, beng one of them the mgraton of legacy transmsson nfrastructures based mostly on TDM and ATM technologes onto a more flexble, effcent IP/MPLS packet nfrastructure for the core network but also for the backhaul 1 part of the rado access network. Such a mgraton would converge the core and rado access networks (RANs) and also would facltate the ntegraton and coexstence of dfferent heterogeneous Rado Access Technologes (RATs) over the same nfrastructure. On the other hand, t s also apparent that such a mgraton creates the challenge to support QoS over such IP networks snce, even though over-provsonng can be the most straghtforward way to manage QoS n the core network, t may not be the case for the backhaul network where one can fnd a predomnance of relatvely low-speed leased lnes and mcrowave rado lnks. In fact, one of the bggest cost challenges facng wreless servce provders today s the backhaul nfrastructure that uses to be very expensve to mantan and dffcult to scale. Furthermore, lmtatons n the backhaul can become more evdent wth the progressve deployment of new hgh speed technologes lke HSPA (Hgh Speed Packet Access) that wll ultmately turn nto a hgher bandwdth provsonng n the backhaul network [1][2]. Hence, n ths context, the development of 1 the part of the network ncludng the cellular base staton at the edge, the base staton controller or rado network controller, and all other Layer 1-3 transport, aggregaton, and swtchng elements n the access and metro networks approprate resource management technques to support QoS n a RAN wth IP-based transport (IP RAN) can result n bg savngs. In ths paper we develop an ntegrated call admsson control (CAC) for IP-RANs that consders both rado and transport resource occupancy n ts decson-makng process. The framework s able of handlng potental bottleneck stuatons n the IP transport part of a RAN. Ths leads to a new paradgm where transport resources are consdered not only at the network dmensonng stage but are ncluded n an ntegrated resource management scheme. Ths new paradgm allows to dynamcally capture wthn the CAC framework multple stuatons where the capacty or occupaton of the transport network can vary over tme (e.g. routng changes due to lnk falure/congeston, a rado cell exceedng ts dmensoned transport capacty to the detrment of other cells, etc). The CAC framework s valdated by analysng a specfc CAC algorthm n the context of UTRAN R'99 wth IP transport. The CAC algorthm s able to consder not only f a partcular QoS bearer request can be admtted or not, but also how t can be admtted (e.g. by properly selectng the rado access bearer capabltes) so that hgher network utlsaton can be acheved. Exstng work on admsson control n the UTRAN has manly focused on transport networks based on ATM and less attenton has been pad to IP transport solutons. Furthermore, prevous research work has been exclusvely addressed by focusng on the transport tself, that s, wthout explotng the possbltes of ntegratng the admsson approach among the rado and the transport [3][4]. The paper s organsed as follows. Secton II dentfes the coordnaton of the rado and IP transport among the key drvers wthn B3G and 4G archtectural network frameworks. Then, n Secton III, a novel resource management model that enables the IP and rado coordnaton for the QoS provson s presented and the proposed CAC dentfed as one of the buldng blocks of such framework. Over such a bass, Secton IV develops the proposed CAC framework and detals a specfc algorthm for UTRAN wth IP-transport. Results are ncluded n Secton V and fnally Secton VI concludes de paper. II. E2E QOS APPROACH FOR EVOLUTIONARY 3GPP-BASED NETWORK ARCHITECTURES A plausble scenaro for B3G networks n the medum term conssts of a heterogeneous access network encompassng UTRAN, GERAN and WLAN RATs deployed over a fully mgrated IP transport nfrastructure [5]. Under ths scenaro, network archtecture and nterfaces between rado equpment (e.g. Iub) would be stll complant to 3GPP releases 5 or 6. In ths context, the scope of end-to-end QoS management solutons over ths archtecture s llustrated n Fg. 1 and encompasses two man aspects: (1) Common

2 Rado Resource Management (C), devoted to coordnate and optmse the usage of the several heterogeneous rado access nterfaces, and (2) rado and IP transport coordnaton, that s, the deployment of QoS control mechansms (e.g. admsson control) consderng both rado and IP transport resource avalablty. The second aspect s especally relevant for the RAN part snce overprovsonng n the backhaul s not seen as a sutable soluton. Rado Network Layer (RNL) Transpot Network Layer (TNL) Mult-mode termnals rado Node-B BTS WLAN AP IP transport Moble network E2E QoS access network IP-based transport MSC RNC BSC GANC SGSN Server C IP transport PSTN/ISDN IP transport CS-MGW IP-based core network Fg. 1 Reference E2E QoS archtecture GGSN IMS Servces External PDN On the other hand, 3GPP s currently specfyng an evolved network archtecture that wll ensure contnued compettveness of the 3GPP technologes n a long-term scenaro. These efforts are manly coordnated by the Long Term Evoluton (LTE) and System Archtecture Evoluton (SAE) [6]. The new network model s pursung a more dstrbuted and packet-optmsed RAN that can ultmately beneft from the adopted mgraton to IP nfrastructures. However, even though the LTE network wll avod the need to support nterfaces wth strngent delay requrements (e.g. Iub n UTRAN) over the IP-based transport network by confnng at the base statons, the moble network wll always show a hgh degree of capllarty to nter-connect a lot of access ponts to the core network, so that the problem of achevng an effcent usage of resources n the transport network wll persst n the longterm evoluton. Thus, bottlenecks may appear n the IP transport n both network scenaros due to backhaul lmtatons and we am at handlng them dynamcally through resource management functons. functons Lnk Rado Packet Schedulng CARM functons RAT Selecton Bearer Selecton Admsson Congeston Moblty TRM functons Route TNL Packet Schedulng Fg. 2. Proposed QoS management functons. III. A FUNCTIONAL REFERENCE QOS FRAMEWORK Ths secton hghlghts the man characterstcs of a functonal framework for a coordnated management of rado and transport resources that leads to effcent resource utlzaton and to better support of QoS guarantees. Ths framework has been ntroduced n [7] and t s referred to as CARM (Coordnated Access Resource Management). The man QoS management functons lkely to be deployed n an IP-RAN, summarzed n Fg. 2, are splt n three categores: CARM, -specfc functons and TRMspecfc functons. CARM refers to those functons where a strong nteracton between rado and transport segments can be predcted, and ncludes RAT Selecton (RS), Admsson (AC), Congeston (CC), Bearer Selecton (BS) and Connecton Moblty (MC). -specfc refers to those functons only related to the rado segment whch only make sense wthn ther own scope (or pool of resources)., and ncludes Rado Lnk (LC) and Rado Packet Schedulng (RPS). Smlarly, TRM-specfc refers to those functons only related to the IP segment, and ncludes TNL Route (RC) and TNL Packet Schedulng (PS). In the next paragraphs the objectves of each of the envsaged functons n the QoS archtecture are descrbed. -RAT selecton: Ths functon s n charge of selectng the most approprate RAT, ether at call establshment or durng the sesson lfe-tme through the so-called vertcal handover procedure, gven the requested servce and QoS profle. -Bearer Selecton: Bearer selecton s n charge of selectng the most approprate rado access bearer servce confguraton accordng to the requested QoS profle. The selecton can rely on rado and transport network load nformaton. -Admsson : mantans nformaton of avalable/allocated resources n both the rado and the IP transport network and performs resource reservaton/allocaton n response to new servce requests, at call establshment or durng vertcal/horzontal handover, wth a gven QoS profle. -Congeston : It s n charge of takng the actons requred to handle overload events n the rado or transport network sde. -Moblty : Ths functon s n charge of assurng a proper dstrbuton of moble termnals among rado cells through the approprate traffc steerng mechansms (e.g. handover). -Rado Lnk : It s n charge of dynamcally adjustng the rado lnk parameters of the moble termnals n order to preserve the QoS for establshed sessons (e.g power control and lnk adaptaton). -Rado Packet Schedulng: Ths functon s n charge of maxmzng resource occupaton by schedulng packets for establshed sessons. -TNL Route : Ths QoS management functon s n charge of selectng the optmum routes n the transport network to guarantee the effcent use of TNL resources and the QoS requested by the TNL IP bearers.

3 -TNL Packet Schedulng: Ths functon s n charge of mplementng, at the IP transport network nodes, the approprate QoS queung decsons so the dfferent flows (or aggregates of flows) receve the rght QoS treatment at every node. It s worth mentonng that the CARM framework fts both the envsaged medum-term archtecture for B3G networks wth IP transport n the RAN [5] and the long-term 3GPP vson where IP nfrastructure s also deployed between evolved NodeB (enb) and access gateways (AGWs) [6]. IV. COORDINATED ADMISSION CONTROL In an heterogeneous network envronment offerng flexble servces, the admsson control should consder, not only f a partcular QoS bearer request can be admtted or not, but also under whch condtons, that s how, t can be admtted (by allowng only certan transport formats, for example, n the case of UTRAN) and n whch RAT and rado access pont, that s where, t could be admtted (assumng that there are several canddates of the same or dfferent RAT). And n the case of an admsson control mechansm ntegratng rado and transport parts, ths decson would be nfluenced by at least (1) the rado resource occupaton n the canddate rado access ponts and the (2) transport resource occupaton n the path between the canddate rado-access ponts are ther correspondng network controllers or access gateways (that s, the next anchor pont n the network behnd the access pont for user plane processng). Rado metrcs If, where, how CARM functons nvolved n the admsson process RAT Selecton Cell Selecton NodeB BTS Bearer Selecton Admsson Low Transport Network metrcs IP transport network Traffc aggregaton level n transport lnks Fg. 3 CARM functons nvolved n the admsson process Hgh RNC BSC Fg. 3 llustrates the scope of the admsson process ntegratng rado and IP segments n a heterogeneous RAT scenaro. As shown n the fgure, the whole admsson control decson s eventually related to the CARM functons RAT selecton, cell selecton and bearer selecton (the frst two functons related to "where" and the last one to "how" admt the connecton). In ths paper the focus s manly targeted to analyse the mpact of consderng the status of the transport network n the admsson process. Then, over such a bass, optmsaton of ths admsson process by dynamcally adaptng the rado bearer confguraton (.e. Bearer Selecton) s also addressed. On the other hand, the benefts of usng RAT and cell selecton consderng transport aspects n the admsson process are out of the scope of ths work. In the followng subsectons we frst descrbe the QoS model assumed for the RAN transport network and afterwards develop an ntegrated CAC for IP-based UTRAN scenaros. A. QoS model of the RAN transport network A dfferentated servces (Dffserv) model s consdered n the IP transport network. Thus, several Per Hop Behavours (PHBs) would exst and rado equpment (.e. NodeB and RNC) wll perform the mappng between rado traffc categores and the PHBs. No bandwdth reservatons are done per NodeB, that s, traffc from several NodeBs traversng a gven IP router compete for the same resources. Notce that ths model does not exclude the utlsaton of MPLS for path management but n any case QoS dfferentaton wthn the forwardng functonalty s entrely handled by Dffserv. On the other hand, the Dffserv model lacks of a standardsed control plane although dfferent approaches have been proposed n the lterature [8][9]. In ths work we assume a model smlar to the Bandwdth Broker concept [8] n the sense that bandwdth management functons (e.g. admsson control) are not ntegrated wthn dffserv routers but are located n a separate entty whch reles on network topology knowledge and measurements montorng to control the use of the network doman. B. Algorthm formulaton To show the feasblty of the proposed ntegrated approach, we develop a CAC algorthm to regulate the amount of nteractve traffc supported over a UMTS R99 network. Transport channel type swtchng s used n the ar nterface so that actve users are assgned Dedcated Channels (DCH) as soon as they have data for transmsson and there are avalable codes [9]. If not, they reman connected through the Forward Access Channel (FACH) n downlnk and Random Access Channel (RACH) n uplnk. We have decded to focus on ths knd of data traffc because of ts hgh varablty, thus makng the admsson control process a dffcult problem when targetng to obtan hgh lnk utlsatons n the transport network wthout connecton performance degradaton. Furthermore, due to the bursty nature of ths traffc, there s a lack of approprate traffc descrptors that prevent the usage of parameter-based admsson control (PBAC) algorthms n front of measurements-based admsson control (MBAC) solutons. Moreover, MBACs schemes relyng only on aggregated bandwdth nformaton n contrast wth usng per-sesson knowledge s appealng from an mplementaton vewpont. The man objectve of the proposed algorthm s to regulate the number of admtted data sessons so that specfc QoS ndcators of on-gong connectons can be stll satsfed. Over such a bass, a complementary objectve s added to the ntegrated algorthm so that the dynamc selecton of the rado bearer capabltes can be exploted. In partcular, the maxmum allowed transmsson rate whle beng n DCH mode s dependent on the occupancy of rado and transport resources. Let s assume that the Rado Access Bearer (RAB) under consderaton allows confgurng K dfferent maxmum data bt rates for the DCH channel. Let's R, =1..K, denote the set of possble rates for DCH confguraton so that R <R +1. Accordng to ths notaton,

4 Fg. 4 llustrates the proposed admsson control approach where a an admsson request s ntally checked wth the hghest R K but, f rado and/or transport lmtatons exsts, a lower R, K, can be fnally decded. Sesson Request Default bearer confguraton (R K ) Rado Measurements R K Rado R m (R m R K ) Admsson Rejected Transport Measurements Transport Admsson R m (R n R m ) Accepted wth R n (n K) Fg. 4. Coordnated Admsson approach. Wth respect to the rado part, downlnk admsson control strateges are usually based on Node-B power consumpton, snce t s the man resource shared between the users connected to the node B. As a result, admsson control strateges based on power estmaton must take nto account whether or not the Node-B has enough power to ensure the agreed QoS requrements of both the new user and the already accepted users. The general expresson of an admsson control based on power estmaton that occurs n the -th frame can be represented by [10]: * PAV [ n] + Pk PT (Eq. 1) where P AV [n] s the averaged Node-B transmtted power n the n-th frame, P k s the estmated power ncrease due to the acceptance of the new user wth rate R k and P * T s a certan admsson threshold. On the other hand, uplnk admsson control s typcally based on cell load factor montorng. Assumng that a gven number of users are already admtted n the system, the admsson control algorthm consders the ncrement n the load factor that the new acceptance would orgnate. Therefore, the condton to be checked for the admttance of the request would be: ηul + η η max (Eq. 2) η UL beng the current estmaton of the uplnk cell load factor, η beng the estmated contrbuton demanded by the user. Now focusng on the transport admsson part, gven a RB request, the transport admsson s sucessfully passed wth the hghest R that satsfes the followng condton: avbw ~ path[ n] δ R (Eq. 3) where avbw path [ n ] s the estmaton of the avalable bandwdth n the I ub nterface for the nteractve traffc class at tme nstant n n the path between a NodeB and ts controllng RNC and δ [0,1] s a factor used to obtan an admsson rate constrant based on the peak rate R ~ of the RB n the transport network (.e. DCH data rate plus transport protocol overheads). It s worth notng here that ths admsson rate constrant, even beng conservatve f δ values close to 1.0 are used, only affects the admsson decson of a new RB because, once t has been accepted, the dependence of future admsson decsons on ths RB s only through ts contrbuton to the measured aggregated bandwdth. The estmaton of the avalable bandwdth n the path RNC- NodeB s based on the followng assumptons. Measurements of the traffc load are conducted by the routers n the transport network on each output nterface. In partcular the number of dequeued bts durng a samplng_perod (T s ) normalsed to the avalable capacty C n bts/s s used to calculate the traffc load. These measurements are dstrbuted by TNL routers (usng e.g. SNMP) each reportng perod (T p ). If multple samples are taken n the same reportng perod, the maxmum value s reported. Possble ranges for T s and T p could be respectvely ms and 500ms-10s. From an mplementaton pont of vew, measurements could be collected n a central entty or drectly delvered to the RNCs. In any case, the entty montorng the measurements can calculate an avalable bandwdth per lnk accordng to the followng expresson: avbw [ n] = C (1 µ [ n] β σ [ n]) (Eq. 4) where µ and σ are, respectvely, estmatons for the mean and standard devaton of the reported traffc load n lnk, and β s a parameter used n order to relate Eq. 4 to the probablty of not exceedng the maxmum lnk utlzaton. Notce that many studes have only concentrated n the measured mean value and do not consder the varance. In our case, as suggested n [11], due to the bursty nature of the consdered traffc, the standard devaton allows to account for the approprate spare of bandwdth needed to absorb fast traffc fluctuaton components that can not be compensated by the admsson or departure of new sessons. Moreover, notce that when the number of connectons traversng a lnk s large, by applyng the Central Lmt Theorem, the lnk utlsaton resultng from the aggregaton of multple statstcally ndependent traffc connectons can be modelled as a Gaussan random varable and the, n that case, the β factor can be analytcally obtaned by lmtng the probablty of reachng full lnk utlsaton p accordng to: 1 µ Q σ Q( β ) = p (Eq. 5) where Q(.) s the complementary cdf of a N(0,1) Gaussan random varable. The averagng process used n the computaton of the mean and standard devaton s related to the tme scale of the traffc fluctuatons we are nterested to follow by means of the admsson process. Accordng to [11] f we want the sesson admsson control to be able to follow sesson dynamcs, there s a crtcal tme scale dctated by how fast sessons depart from the system. Ths crtcal tme scale depends on the mean sesson duraton and on the number of smultaneous sessons concurrng n a gven lnk. In partcular, the mean and standard devaton estmators used to track the admsson process are based on the Exponental Weghted Movng Average (EWMA) mechansm and can be defned as follows: µ [ n] = ωµ load[ n] + (1 ωµ ) µ [ n 1] (Eq. 6) σ [ n] = ωσ load[ n] µ [ n 1] + (1 ωσ ) σ [ n 1] (Eq. 7)

5 where the correspondng exponental averagng weghts can be calculated n terms of a gven averagng perod (T av ) as follows: 2 2 wµ =, w T σ = (Eq. 8) av K Tav Tp Tp where K>>1 s used to obtan a more accurate estmaton of the standard devaton over several mean averagng perods. Fnally, from the avalable bandwdth computer per lnk, an estmaton of the avalable bandwdth per path can be obtaned by makng the lmtatons of a potental bottleneck lnk to preval over others by means of the followng expresson: avbw path ( avbw [ n] ) [ n] = mn (Eq. 9) lnk path From an mplementaton pont of vew, notce that the nformaton about whch lnks traverses a RNC-NodeB path can be obtaned by lstenng to OSPF routng protocol messages (RFC2328) to know network topology. V. RESULTS Results are provded n ths secton to demonstrate the benefts of the proposed CAC framework n IP-RAN scenaros wth bottleneck lnks n the transport network. In partcular the followng smulaton cases are consdered: No CAC n the transport. Only rado-aware CAC s performed at sesson set up. CAC A: Coordnated CAC at sesson set up. Admtted sessons make use of 384 kbps data rates n DCH mode. CAC B: Coordnated CAC done at transport channel type swtchng level. In ths case, nteractve sessons are always admtted at call set up but the actvaton of DCH channels durng actvty perods s controlled by the coordnated admsson control. Only 384 kbps DCH channels are granted. CAC C: Smlar to CAC B wth the addton of the bearer adaptaton functonalty. Thus, n ths case, unlke CAC B, the rate of the DCH channel s adapted to transport load status accordng to the algorthm llustrated n Fg.4. Besdes 384kbps data rate, 256 kbps and 128 kbps DCHs can be assgned. Regardng network topology, we consder a basc deployment scenaro consstng of seven hexagonal cells connected to a IP-based transport network wth two traffc aggregaton ponts between each NodeB and ts controllng RNC. Ths confguraton allows us to defne dfferent network scenaros dependng on the placement of the bottleneck lnk. Results provded n ths paper correspond to a bottleneck lnk located between the central NodeB and the frst IP router for traffc aggregaton. The smulaton of the Iub model has been done accordng to gudelnes provded n [5]. In partcular, a layer 3 multplexng scheme has been consdered along wth a packetser that can retan a data fragment as long as 5ms to avod sendng IP packets wth a short payload. The maxmum sze of IP packets s 1500bytes and the buffer szes n the routers are confgured so that a maxmum queung delay of 50ms s tolerated snce, f network buffers are dmensoned too large (e.g. to ensure that no packets are dropped at any transport element), then packets can be fnally dropped at the destnaton node because they have exceeded a maxmum transfer delay [12]. Wth respect to the ar nterface settngs, cell radus and NodeB power level are set so that rado admsson blockng s neglgble [10]. Thus, admsson rejectons are exclusvely due to transport lmtatons. Results have been obtaned for a range of nteractve users unformly dstrbuted n the overall scenaro and a bottleneck lnk capacty of 1 Mbps n the Iub transport of the reference NodeB. Interactve users follow the web browsng model, wth 5 pages per sesson, an average readng tme between pages of 15s, an average of 25 objects (packets) per page, and nter-arrval packet tme of 6.1ms. The average packet sze s 366 bytes. Ths leads to an average bt rate feedng the RNC buffers durng actvty perods of around 480 kb/s and a mean sesson bt rate around 4.8kbps. The mean sesson duraton s around 75s and a sesson arrval rate of 40 sessons/h/user s assumed. Fgure 5 shows the rato of lost transport frames due to buffer overflow n the bottleneck lnk. As shown n the fgure, f no transport-aware CAC s used, unacceptable packet droppng can be caused n the transport network due to the hgh varablty of the consdered traffc. On the other hand, accordng to Fgure 6, mean packet delay observed by nteractve traffc s not too much affected by ths droppng rato due to the relatvely fast retransmsson recovery procedure conducted at the RLC (Rado Lnk ) layer. However, ths droppng rato has repercussons drectly on the amount of extra traffc that the RNC s njectng nto the transport network to recover from transport losses and, as a consequence, there s a traffc ncrease equvalent to the bottleneck droppng rato n all the lnks located upstream between the bottleneck and the RNC controller. Moreover, f no traffc dfferentaton s done at the transport network (e.g. best-effort IP transport network) and real-tme traffc (e.g. voce) s sent n unacknowledged mode along wth data traffc, the droppng rato produced n the transport would be drectly translated nto frame loss rato of the real-tme servce. It s mportant to stress here that ths hgh droppng probablty s observed even for very low lnk utlsatons (e.g. 35% for 320 users n the overall scenaro) due to the bursty nature of the web traffc. Over such a bass, the ultmate goal that the transport-aware CAC need to accomplsh s the reducton of the packet droppng rato n the transport network whle keepng nteractve servce performance ndcators (.e. mean packet delay n our analyss). In ths sense, as shown n fgure 5, CAC A strategy appled at sesson level can lead to a reduced droppng rato by lmtng the number of admtted sessons n the system. A measurement reportng perod T p =1s and no admsson rate constrant has been consdered (δ=0) n ths case. Moreover, ths strategy can provde an mprovement n terms of mean packet delay for admtted nteractve users (see Fgure 6). However, the penalty mposed by ths strategy n terms of admsson acceptance rato s too hgh, as llustrated n Fgure 7. Agan, the reason behnd such reduced admsson acceptance rato s the hgh varablty observed n the web traffc n lnks wth low traffc aggregaton level such as the one addressed n ths study.

6 Transport Frame Loss Rato (%) Mean Interactve Packet Delay (s) No CAC CAC A (p=95%) CAC A (p=99.9%) CAC B (p=50%) CAC B (p=95%) CAC C (p=50%) CAC C (p=95%) Interactve Users Fg. 5. Transport Frame Loss Rato n the bottleneck lnk No CAC CAC A (p=95%) CAC A (p=99.9%) CAC B (p=50%) CAC B (p=95%) CAC C (p=50%) CAC C (p=95%) Interactve Users Fg. 6. Mean packet delay for nteractve traffc n reference NodeB. Admsson Sesson Acceptance Rato (%) No CAC CAC A (p=95%) CAC A (p=99.9%) CAC B (p=50%) CAC B (p=95%) CAC C (p=50%) CAC C (p=95%) Interactve Users Fg. 7. Admsson acceptance rato for web sessons. On the other hand, when movng admsson process at DCH level as proposed n CAC B and C, satsfactory results can be obtaned n terms of mean packet delay and packet droppng whle handlng the same number of users as n the non CAC stuaton (e.g. sessons are always accepted at call set up). In ths case, T p has been reduced to 200ms to account for the fast varaton of the DCH holdng tme and an admsson rate constrant equal to half the peak rate s consdered (δ=0.5). Notce that wth both strateges droppng ratos below 1% can be acheved n the bottleneck lnk for p=95%. Ths reducton has assocated an unavodable cost n terms of nteractve packet delay because DCH actvaton can be delayed due to transport overload. However, when usng the adaptve bearer selecton strategy consdered n CAC C, ths cost can be mnmsed as shown n Fgure 6. In partcular, a CAC C strategy wth p=90% and 380 users s able to reduce transport losses from 7.5% to 0.8% at expenses of a small mean packet delay ncrease from 170ms to 206ms. Moreover, a more aggressve CAC C strategy wth p=50% can even reduce droppng n the transport from 7.5% down to 2.2% wthout affectng mean packet delay performance. CONCLUSIONS Ths paper develops a coordnated CAC framework that consders both the rado nterface and also the IP transport network. Ths leads to a new paradgm where transport resources are consdered not only at the network dmensonng stage but are ncluded n an ntegrated resource management scheme. The ratonale of such a framework s based n the mpractcablty of bandwdth overprovsonng solutons wthn the IP-based transport network nfrastructures for the backhaul part of the rado access network. Ths stuaton s a realty n current 3G network deployments and s expected to persst n next generaton networks. The CAC framework s valdated by analysng a specfc CAC algorthm n the context of UTRAN wth IP-based transport. ACKNOWLEDGEMENTS Ths work s part of the EU IST-AROMA project, [13], partally funded by the EC under the IST framework. Ths work s also partally supported by Spansh Natonal Scence Councl under grant TEC REFERENCES [1] A.Bolle, H.Hertbertsson, Backhaul must make room for HSDPA, Wreless Europe, Feb/Mar 2006 [2] Csco systems, Csco IP RAN Optmzaton Soluton, 2005 [3] G.Fodor et al. Comparson of Call Admsson Algorthms n ATM/AAL2 Based 3rd Generaton Moble Access Networks,1999 [4] S. Malomsoky et al., Connecton admsson control n the UTRAN transport network, Journal Telecommuncaton Systems, Sprnger, Volume 28, Number 1 / January, [5] 3GPP TR v5.4.0, IP transport n UTRAN, Dec [6] 3GPP TR v7.0.0, Feasblty study for evolved Unversal Terrestral Rado Access (UTRA) and Unversal Terrestral Rado Access Network (UTRAN) (Release 7). [7] J. Olmos et al. A Functonal End-to-End QoS Archtecture Enablng Rado and IP Transport Coordnaton, accepted for publcaton n IEEE WCNC2007. [8] R. Nelson et alt., A dscusson of bandwdth broker requrements for Internet2 Qbone, avalable onlne on [9] G. Hejenk et alt. Dffserv resource management n p-based rado access networks, n WPMC 01, September [10] J. Perez-Romero, O. Sallent, R. Agust, M.A. Daz-Guerra, Rado Resource Management Strateges n UMTS, Ed. John Wley & Sons, 2005 [11] M. Grossglauser and D. Tse, A tme-scale decomposton approach to measurement-based admsson control, IEEE/ACM Trans. on Networkng, vol 11, no 4, August [12] 3GPP TS v7.0.0, Synchronsaton n UTRAN Stage 2 (Release 7) [13] IST-AROMA project web page