Multiuser Scheduling with Multi Radio AccessSelectionRiccardo Veronesi

Consorzio Ferrara Ricerche (CFR)Dipartimento di Ingegneria, Universita di Ferrara

Ferrara, ItalyEmail: rveronesi@ing.unife.it

Abstract- In this paper we address the problem of multiuserscheduling with multi-radio access selection, i.e., the data flow ofa given user can be scheduled over multiple radio access technolo-gies of different operators. We will show that performance gainsare possible and come from multiuser diversity as well as multi-radio diversity, as both the best user and the best radio accesscan be selected, at any given time, to get to optimal performance.We compare a terminal-based strategy where users compete tochoose the best Radio Access, and a network-based case wherethe network choose the users to serve at a given time. This workassesses the performance gain due to both multi radio access andmultiuser diversity with respect to the no-multi-radio case, whereusers are constrained to connect to the same single radio access.

I. INTRODUCTION

Future networks will enable wireless terminal to connect toseveral radio access technologies (RATs), like UMTS, WiFi,GPRS, WiMax, etc, of different and even competing networkoperators in a transparent way, thus achieving benefits in termsof enhanced service availability and variety, coverage, lowercosts, bit rates, system capacity etc. This new networkingconcept, which enables and exploits the cooperation of het-erogeneous networks, which can belong to multiple operatorsand technologies, is referred to as "ambient network" [1].The availability of multiple Radio Accesses (RAs) permits

to do radio resource management in a more efficient way, forexample balancing traffic among different RAs, based on radiocost and traffic load, allowing higher trunking gain [2].

Multi Radio Resource Management (MRRM) [3] is there-fore thought and designed to this aim and includes severaltopics and design issues: we focus on this work on Multi RadioAccess Selection (MRAS).

Multi Radio Access Selection manages the access of wire-less terminals to multiple networks. The main benefits are-multi-access diversity and multi-access combining [3]: themulti-access diversity permits for a given user to choose fromseveral RAs while the multi access combining simultaneouslycombines transmission over several RAs. Performance im-provement is in terms of enhanced coverage and capacity,overall resource efficiency (costs, QoS requirements, etc) andadditional services.

The literature on this topic is very recent ([4], [6], [7],[8], [9], [10]).In [4] the Authors propose schemes to controland distribute traffic over two different radio access networks,namely GPRS and UMTS, with the aim of optimizing spec-trum efficiency: mobile terminals are served by the optimumRAT available, based on system load, resource availability andthe estimated resource consumption, with the constraint thatthe user traffic is assigned to a single RA at a time. Othertechniques for radio access selection has been very recentlyproposed in [6], [7], considering criteria for access selectionbased on signal strength (coverage), load and resource cost.In particular, in [6] data traffic was assigned to WCDMA orWLAN and traffic hot-spots have been considered, whereas[7] has taken into account RA selection between GERAN,WCDMA and WLAN access systems, focusing also on gainsdue to collaboration among different network operators. More-over, in [8] a joint scheduling algorithm splitting traffic be-tween a UMTS and HiperLan/2 systems was proposed. Thepaper [9] discusses how to assign multiple bearer servicesonto different sub-systems in a multi-access wireless system,and provides several analytical results, which however do notconsider fast time dynamics. Finally, the paper [11] deals withthe comparison between a non-cooperative and a coopera-tive approach between RAs and explores the possibilities ofimprovements achievable by allowing allocation on differentRAs.

This work focuses on joint user-scheduling and radio ac-cess selection strategies, which therefore take advantage ofboth multi-radio and multiuser diversity: multiuser diversity isexploited when a channel aware scheduler selects for trans-mission the user with for example the best channel conditionsor achievable rate (due to the uncorrelated fast fading processacross the users which share the common channel [5]), whereasmulti-radio transmission diversity (MRTD) exploits diversityby selecting the best radio access according to similar criteria,like best channel, highest instantaneous capacity, requestedservice or lowest actual load or cost.We consider here the case of fast radio-access selection, as

in [10], where the selection of the RA is on the same time scaleof user-scheduling. In [10], effective user scheduling and RA

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allocation mechanisms has been proposed, with considerablebenefits over the case where MRTD is not present.

Here, we propose two MRAS strategies: a network basedstrategy where each RA chooses the user to schedule ateach time, based on channel conditions and users currentneed compared to the requested QoS, and a terminal basedstrategy, where each terminal chooses the preferred RA on thebasis of RA capacity and channel condition: then, each RAselects among the candidate users the one with the highesturgency. In both strategies each RA acts independently ofeach other. Network based strategy takes advantage of bothmultiuser diversity (by choosing the "best" user) and multi-radio diversity (users connected to more RAs can receive dataflows from multiple RAs), whereas in terminal based policyonly multi-radio diversity can be exploited.

With respect to the work in [10] the scheduling and al-location strategies proposed here consider the case of RAswith different capacities and users with different requestedQoS (expressed here in term of received bit-rate), so that thisheterogeneity has to be managed in the fairest possible waybetween the users. Besides, with respect to [10] each RA actsindependently of each other in the RAs-to-users allocation:this is allowed by the fact that for instance two RAs areallowed to serve the same user terminal in the same time-slot, if both of them elect it as the best one. This is referredto as parallel multi-radio transmission diversity as opposed toswitched MRTD, which is considered in [10], where each usercan be served by only one RA at a time. The advantage isin terms of reduced complexity due to independent allocation,whereas the RA allocation is not optimized jointly betweenRAs and all terminal equipments must support parallel MRTD.

Results obtained in this paper show a substantial improve-ment in terms of user-throughput from multi-radio accessdiversity. This gain is higher if multiuser diversity can notbe exploited.

II. SYSTEM MODEL

The downlink of a single cell system with U users isconsidered. However, the same results can be applied tothe uplink. Each user-terminal is assumed to support all theavailable L RAs. Time is divided in time slots.

Each RA has an available bandwidth W(l), which corre-sponds to a symbol rate R(l). RAs are assumed to operate ondifferent frequencies so that they do not interfere with eachother. The transmit bit rate is defined as Rb(l) = R(l)c(l)where c(l) is the number of bits per symbol. Simulation resultsconsiders L = 4 radio accesses with 3 different values forR(1), as illustrated in Table I. If the RA uses variable rateadaptive techniques then

Rb(l, s) = R(l)c(l, m(s)) (1)where s is a given time slot and in(s) the transmission modeused in slot s. Channel model includes path loss, shadowing

TABLE IRATES OF THE AVAILABLE RADIO ACCESSES.

RA id I 1 2 3 |4

Rl (Mbaud/s) 4 8 16 | 16

and frequency flat Rayleigh fading, independent on eachcouple RA-user. Each RA is capable of a "slow" power control,which equalizes long term channel variations, i.e. path loss andshadowing components. Hence, for the couple RA I - user uthe signal-to-noise ratio (SNR) a is expressed as

1~,U = Yoriu

where rl,u is the random Rayleigh fading gain, modeled asan exponentially distributed random value with unitary mean.Fading is supposed constant on each time slot, whereas itchanges slot by slot. The average SNR 'yo instead remainsconstant. The average user throughput in the current slot s isdefined as

I S L(U, S) =-E E , (i)Rb(1, i)fl(l.(i))

i=-l 1=1(2)

where

* q$,u(i) is the fraction of RA rate assigned to user u onslot i, with the constraint EU ¢bz,(i) < 1.

if(-y) is the probability that a packet is successfullyreceived.f, ('t) can depend on several parameters (mod-ulation, coding etc).

In order to have a less complicated problem formulation, weconsider the case where in each time slot a RA can be assignedto only one user. However, a user can be assigned more RAsin the same slot. This translates to I1,u (s) = 1 if RA 1 isassigned to user u in slot s, 0 otherwise.

In this paper, we compare the case of BPSK modulationand adaptive modulation. In fact, in a channel dependentscheduling, adaptive modulation and adaptive modulation andcoding (AMC) can considerably improve performance. At thisstep, we consider uncoded packets, independent errors andpackets of N bits, so that

f (a)= I - a(l,m)erfc(N

(3)

where ar(l, m), 3(1,m), c(l, in) depend on the modulation.We consider here BPSK and M-QAM, with M = 4,16, 64.Hence, c(l) can assume the values 1, 2,4,6 respectively. Onthe consequence, for the computation of (2)

Rb(l, i)fl (Y1,u (i)) =N/c(l,m)

max R(l)c(l, m) 1- a(1, m)erfc( 13(1,m

(4)

456

TABLE IITARGET RATE (IN MBIT/S) REQUIRED BY THE USERS AND PROBABILITY

OF A USER TO REQUIRE RATE 77th-j (Pj = Prob{nth(u) = 7th-j})

7lth-1 |lth-2 | th-3 P1 P2 P30.5 1 4 1/3 T 1/3 1/3

We assume "greedy" users (and packet queues always full)which try to get all the available rate. However, each userrequires a target average rate Tith(u) which depends on theservice required. We consider here 3 types of services with3 different target rates ?7th-1,7th-2,1th-3. Each user is ran-domly assigned only one of the three target rates according tothe distribution displayed in Table II (pi = Prob{l7th(U) =77th-1 } ).

III. SCHEDULING STRATEGIES

Two scheduling strategies, namely network and terminalbased are considered here in order to assess the gain obtainedfrom multi-radio access selection. We compare the case ofMRAS, where each user can connect to every RA, with thecase of no MRAS, where each user is constrained to connectalways to the same RA l. These strategies are based ona selection criterion aimed at optimizing the average userthroughput normalized to the request, i.e.

((U, S) = 7(U, S)/lth (U). (5)Since we assume always active RAs and "greedy" users,((u, s) can exceed 1 at low loads. Hence, to assess the gradeof satisfaction of a user we define

~(u, s) = min(((u, s), 1). (6)In the network based strategy the choice of the user to scheduleat a given time slot s is taken by the network, whereas in theterminal based strategy, each terminal contends to access thenetwork in a given time slot and decide which RA to choose.The network based strategy exploits both multiuser and

multi-radio diversity, since the network decides the users toschedule at a given time. Conversely, in the terminal basedaccess selection, the terminal decides to which RA to connectto and therefore only multi-radio diversity can be exploited.Both strategies are compared with the case where MRAS isnot available. With no MRAS, each user is pre-assigned to agiven RA and obviously multi-radio diversity is not possible:however with the network based strategy each RA still canexploit multiuser diversity since the best user is chosen amongthe users assigned to the RA itself. Instead, with the terminalbased strategy each user in each slot try to get access to itsown pre-assigned RA but only one of them (according to itspriority) will get access to the RA. Hence, no diversity ispresent. Both strategies are described in detail in the followingsubsections.

A. Network based strategy

In each slot, each RA decides which user to serve amongall the U users. It is allowed that more than one RA can selectthe same user at the same time, but each RA can be assignedto only one user. At each slot s each RA 1, independently ofeach other, chooses the user terminal u which maximizes

(7)Rb (1, S)fl (-1), (S))

((u, s - 1)The rationale of this decision criterion is the following:

if all the users required the same target rate and had thesame average channel conditions, the best choice would bethat each RA serves in each slot the user with the maximumexpected rate Rb(l, s)fl(y1,u (s)). With users with differentaverage channel conditions a good policy is to serve user withthe best channel normalized to the average channel condition.This scheduling is called proportional fair scheduling. In ourcase all the users have the same 'yo but different QoS requests,hence the scheduler has to prioritize somehow users withhigher requested rate, but taking into account channel stateas well. This is obtained by means of the criterion in (7): eachRA schedule in a given slot the terminal which maximizes theexpected received rate with respect to its "need", expressed by((u, s).

This case is compared with the case where MRAS is notavailable: the algorithm is the same but the RA 1 chooses onlyamong those users initially assigned to it, instead of betweenall the U users in the system. In the MRAS case multiuserdiversity is more effective since the best user is chosen on awider set of users: moreover, load balancing is possible sincea less loaded RA can serve users of a more loaded RA.

B. Terminal based strategyIn each slot s, each user tries to connect to the RA 1 which

maximizesRb (1, S) fl (1,u (S) ).

Then, from the set of users that have selected RA 1, the userwith the higher priority (measured with ((u, s-1)) is selectedto be served by RA 1 in slot s. Hence, multi-radio diversity isexploited, whereas multiuser diversity is not. In the no-MRAScase, each user terminal is forced to choose its own RA. Soin this last case neither multiuser nor multi-radio diversity ispresent.

IV. NUMERICAL RESULTSEach point on the figures is obtained by averaging a suitable

number of independent simulation runs of S = 4000 slotseach. In each simulation run, the target rates rlth (U) arerandomly assigned to the users according to the probabilitiesshown in Table II and remain constant during the simulationrun. Then, for the no-MRAS case, each user u is assigneda RA lu according to rlth(u): users requiring llth(U) = '1th-1

457

12 18 24 30 36 42 48 54 60

Number of users

Fig. 1. User satisfaction vs number of users. BPSK modulation.

belongs to RA 1, users with 7Jth(U) = 77th-2 to RA 2, whereasusers requiring 71th-3 are randomly assigned to either RA 3or RA 4 with probability 0.5. For a fair comparison with theMRAS case, probabilities and target rates in Table II have beenchosen to have a statistically balanced load among RAs whenMRAS is not used. In fact, for RA 1 we have p1th_1/R1 =(1/3 0.05)/4 = 1/24, for RA 2 (1/3.1)/8 = 1/24, for RA 3and 4 (1/3 1/2. 4)/16-= 1/24.

Fig. 1 shows performance comparison among the case ofnetwork and terminal based scheduling with BPSK modula-tion. User satisfaction ~(n, S) is plotted versus the number ofusers in the system. It can be noted that the network basedtechnique achieves the best performance. At the same time,the gain of MRAS over the case of no MRAS tends to reduceat high loads. In fact one of the advantages of network basedMRAS is that multiuser diversity is exploited on the wholeset of users, whereas with no MRAS multiuser diversity canrely only on the users initially assigned to each RA. With manyusers, however, even without MRAS, multiuser scheduling canspan over a sufficiently large set of users to have a sufficientgrade of diversity against channel fluctuations, as will beexplained later. Hence, the gain with respect to the MRAScase is more limited. As far as the terminal based policy isconcerned, with no-MRAS each user is forced to always selectits own RA, whereas with MRAS the user selects the best RA.In this case the improvement margin is larger since the benefitof multiuser diversity is not present.

Fig. 2 shows the same case of Fig. 1 but with adaptive mod-ulation instead of BPSK. It can be noted the huge performanceimprovement: in fact adaptive techniques can very effectivelytake advantage of channel aware scheduling and resourceallocation. Moreover it can be noted that also in this casescheduling with MRAS achieves a considerable gain over thecase where MRAS is not used. Moreover, multiuser diversityis exploited very effectively thanks to adaptive modulation andtherefore the gap between network based and terminal based

0.E

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0.:

no MOASN Network based -MOAN Network based --

no MOAN Terminal based--MOAN Terminal based 5--

12 10 24 30 36 42 40 54 0

Number of users

Fig. 2. User satisfaction vs number of users. Adaptive modulation.

policies is more evident than in the BPSK case. Fig. 3 showsthe impact of the average signal to noise ratio -yo, for the caseof 42 users and RA with adaptive modulation. First, it can benoted that that network based MRAS is very effective evenwith a low tyo: this is due to diversity over users and radioaccesses. It can be also seen that as 70 increases, the gapwith respect no MRAS tends to reduce. In fact, as mentionedbefore, the network based policy with no MRAS is still able totake advantage from multiuser diversity although on a limitedset of users. However, when the channel is on average verygood, multiuser diversity is no more very useful to copewith channel fluctuations, although the advantages remains interms of load balancing: when a RA is less loaded, it can beused to serve terminals belonging to other RAs also. This isconfirmed also by the fact that as -yo increases performanceof the terminal based policy, which does not exploit multiuserdiversity, get closer to the network based one. However, in oursimulations we have taken probabilities which assign users toRAs in a statistically balanced way, so although the actualload is not perfectly the same on all RAs during the no-MRAS simulations, the differences are little. Hence, a muchmore evident effect of load balancing capabilities would befound if some RAs were overloaded with respect to others.Finally, to confirm this conclusions, it can be noted that inspite of network based policy, the terminal based allocationmaintains a consistent performance gap between no MRASand MRAS as -yo increases. Figure 4 depicts the performanceof users of different service classes. The metric is the averageuser throughput r7(u,S). It can be noted that, as expected,throughput decreases as load increases. The requested ratesare all satisfied for all classes, except for the highest loadwhere, however, the requirements are almost satisfied: it isworth noting that the proposed algorithm keeps the load evenlyshared among traffic classes, without sacrificing one of them.In fact, a part of capacity could be achieved by penalizing themost demanding users. Moreover, by comparing scheduling

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--------------

24 30 36 42Number of users

48 54 60

Fig. 3. Impact of the average SNR. Adaptive modulation.

algorithms with and without MRAS, it can be noted again thatthe introduction of multi-radio diversity increases capacity ofall user-classes, without achieving gains at the expenses of oneof them, although the scheduler gives more rate to the mostdemanding class (but being the other two already above therequested threshold.) Only for 60 users the 4 Mbit/s class isslightly under the requested rate, whereas the other two stillachieve the target.

V. CONCLUSIONSTwo scheduling strategies which exploit Multi Radio Access

Selection have been proposed. The gains due to multiuserand multi-radio diversity have been shown and both terminaland network based access selection exhibited very significantgains with respect to the case where MRAS is not used. Themost efficient is the network based one, which also exploitsmultiuser diversity, although when the propagation conditionsare good and the number of users per RA increases, theimprovement due to MRAS is mainly due to load balancingrather than to diversity against channel fluctuations.

VI. ACKNOWLEDGEMENTS

Special thanks to Prof. Velio Tralli, Leonardo Badia (CFR,University of Ferrara, Italy), Aurelian Bria (Royal Institute ofTechnology, Stockholm), Francesco Meago (Siemens Mobile,Italy) for valuable comments and suggestions. This paper

describes work undertaken in the context of the AmbientNetworks project which is part of the EU's IST program. Theviews and conclusions contained herein are those of the authorand should not be interpreted as necessarily representing theAmbient Networks Project.

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