an adaptive random access strategy for multi-channel relaying networks

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An adaptive random access strategy for multi-

channel relaying networks

JIANG Fan†, TIAN Hui & ZHANG Ping

Key Laboratory of Universal Wireless Communications, Ministry of Education, Wireless Technology Innovation Institute, Beijing Uni-

versity of Posts and Telecommunications, Beijing 100876, China

In this paper, an adaptive random access strategy is presented for multi-channel relaying networks toaddress the issue of random access of the non-real-time (NRT) services. In the proposed scheme, NRTservices access the base station (BS) by first accessing the nearest relay node (RN). When collisionoccurs, for the sake of fast and efficient access, the user will begin a frequency domain backoff ratherthan randomly retry in time domain. A remarkable feature of this scheme is that the RN will adaptivelydetermine the maximum allowed frequency backoff window at each access period. This is achievedaccording to the new arrival rate as well as the number of available access channels. Moreover, to al-leviate the interference caused by sub-channel reuse among RNs, a fractional frequency reuse schemeis also considered. The analysis and numerical results demonstrate that our scheme achieves higherthroughput, lower collision probability and lower access delay than conventional slotted Aloha as wellas the scheme without frequency backoff window adaptation.

multi-channel relay, random access, backoff policies, interference coordination

1 Introduction

The cooperative relaying networks, which is def-initely an option of the future B3G/4G networkstructure, is providing a pretty new direction fornext generation mobile communications[1]. As anindispensable component, random access strategiesplay an important role in the uplink scheduling aswell as initial access and short message transmis-sion.

In order to relieve packet collision in the courseof random access, a voluminous number of re-searches have already been investigated. Ref. [2]

proposed a differentiated backoff strategy for pro-viding priority for cellular networks, and devel-oped an infinite population model and derived theoptimum retransmission probabilities under differ-ent retransmission policies. Cho et al.[3] discusseda multi-channel random access protocol based onslotted Aloha for multi-hop cellular systems. Theysuggested an optimal partition ratio of shared ran-dom access channels between a base station anda relay station. To address the issue of randomaccess in multi-channel environment, Choi et al.[4]

provided a fast retrial scheme that adopted randomfrequency retrials under the structure of OFDMA.

Received May 22, 2009; accepted August 24, 2009

doi: 10.1007/s11432-009-0218-2†Corresponding author (email: [email protected])

Supported by the National High-Tech Research & Development Program of China (Grant No. 2009AA01Z262), the National Basic Research

Program of China (Grant No. 2009CB320400), and the National Natural Science Foundation of China (Grant No. 60832009)

Citation: Jiang F, Tian H, Zhang P. An adaptive random access strategy for multi-channel relaying networks. Sci China Ser F-Inf Sci, 2009,

52(12): 2406–2414, doi: 10.1007/s11432-009-0218-2

Nevertheless, the proposed scheme could hardlyadapt to the situation with varying load. More-over, most of the aforementioned studies treatedthe random access protocols as a means of access-ing the network; hence, little attention has beengiven to the quality of service (QoS) at the accessphase. In order to provide QoS guarantees, Yanget al.[5] proposed a service differentiation access al-gorithm for multi-channel cooperative relaying net-works. However, one of the limitations concernedwith this study is that the NRT requests will un-dergo an excessive amount of access delay due touniform backoff retransmission policy adopted byeach user.

To this end, an adaptive multi-channel ran-dom access strategy (AMRAS) is developed formulti-channel relaying networks. In our proposedscheme, users with non-real-time (NRT) requestwill send their packets to the nearest RN insteadof directly accessing the BS. Based on the informa-tion received from the RN, once the initial randomaccess fails, NRT services will immediately begina random frequency sub-channel selection insteadof conventional time domain backoff. The RN will,on the other hand, dynamically decide the optimalmaximum allowed frequency backoff window at thebeginning of each access period. Moreover, to alle-viate the interference caused by sub-channel reuseamong RNs, a fractional frequency reuse scheme isalso suggested to be adopted.

The remainder of this paper is organized as fol-lows. Section 2 presents the system model anddescription of AMRAS. The proposed AMRAS isthen analyzed explicitly in section 3, and the per-formance evaluations are provided in section 4.Section 5 concludes this paper.

2 System model and description of AM-RAS

Take a two-hop fixed relay based cellular net-work employing orthogonal frequency division mul-tiplexing access (OFDMA) physical-layer as an ex-ample of the multi-channel environments. The as-sumption is that users with real-time (RT) serviceswill directly transmit the request packets to the BSwhile the NRT requests will access the BS through

the nearest RNs. For the sake of service differ-entiation and quality of service (QoS) provision,all the random access channels (RACH) adoptedare divided into two parts: the RT indicator chan-nels (ICH) and packet access channels (PACH)[5].Assume that there are altogether N RACH chan-nels in the system. One user with RT service ran-domly selects an ICH channel to request for an ex-clusive access channel. Once the user has success-fully transmitted this packet, the BS recognizes thechannel request and reserves a collision-free PACHchannel whenever it has sufficient resources to at-tend this petition. Since this paper mainly dealswith the random access scheme with NRT services,in the rest of this paper, we will only focus on theperformances of NRT services.

After a round of RT reservations, the NRT ser-vices will compete for the rest of the PACH chan-nels. Here, it is supposed that the remaining PACHchannels can be completely reused among differentRNs without interference if perfect power controlis employed at RNs. When a user has NRT ser-vice to send, it sends a channel request messageimmediately to the nearest RN. If the RN receivesthe request successfully, it broadcasts the assign-ment result through an uplink map in the nextframe. If unfortunately, the random access fails,which is mainly caused by collision, the user be-gins a frequency domain backoff by randomly ac-cessing another available PACH channel instead ofconventional time domain backoff. After the NRTrequests are collected, RNs will send these requestsback to the BS in subsequent access slots with ac-cess channels. These channels are preserved afterthe RT reservation and can be pre-allocated by theBS based on the distribution of NRT loads.

In AMRAS algorithm, a maximum backoff win-dow W is preset at each access period which lim-its the maximum retries for which a user is al-lowed through frequency domain backoff. That isto say, if exceeding the maximum attempts, AM-RAS gets back to the 1-persistent slotted Aloha inthe time domain. The length of W is adaptivelydecided and updated by the RN according to thecurrent user arrival rate as well as the number ofPACH channels left. More specifically, when theload is relatively light or moderate and there are

JIANG F et al. Sci China Ser F-Inf Sci | Dec. 2009 | vol. 52 | no. 12 | 2406-2414 2407

enough PACH channels for access, an NRT ser-vice experiencing collision is permitted to make anumber of retrials by random PACH channels se-lection in order to access sooner. On the otherhand, with the object of fast access, the NRT ser-vice under heavy load is advised to end frequencybackoff earlier and start time domain retransmis-sion in the 1-persistent manner. Furthermore,for heavy load case, additional collision resolutionalgorithms such as p-persistent or non-persistentalgorithm might be needed to effectively reducecontention[6,7]. Nonetheless, under multiple ran-dom access channel environments with moderateload, the proposed AMRAS strategy achieves bothfast access and high utilization for NRT services.

However, if effective power control is unavailable,we further propose to employ a fractional frequencyreuse technique to mitigate the strong interferencecaused by fully sharing of the remaining randomaccess channels. Through frequency planning inadvance, server interference among RNs can beprecluded. A detailed investigation and interfer-ence evaluation are provided in section 3.

3 Analytical performances and interfer-ence evaluation

3.1 Analytical performances withoutconsidering interference

In this section, the working process and perfor-mances of AMRAS without considering the inter-ference are first elaborated. It is assumed that fullchannel sharing among the RNs is free of interfer-ence, which gives the premise that effective powercontrol policy is adopted at each RN. Moreover, itis supposed that the transmission channel is in anideal state in that packet transmission error is onlycaused by collision. We first define some notations.These notations will be helpful to analytically ob-taining access throughput, collision probability andaccess delay probabilities.

N : number of random access channels;r: the number of RNs;G1 and G2: the combined rate of new and back-

logged arrivals for RT and NRT services, respec-tively (the backlogged arrivals for NRT service

come from both time domain as well as frequencydomain);

R: the number of remaining PACH channels af-ter RT reservation;

T1 and T2: the throughput of RT and NRT ser-vices, respectively;

p: user collision probability (ratio of collisions tototal number of frequency domain backoff);

W : the size of maximum allowed frequency back-off window;

Gnew: combined rate of new and time domainbacklogged arrivals for NRT services.

To simplify analysis, it is assumed that the totalof the new and backlogged arrivals in one accessslot follows a Poisson distribution with rates G1

and G2, respectively, for the RT and NRT services.Besides, the RNs and users are supposed to dis-tribute uniformly within the cell.

For RT services, assuming that N access chan-nels are independent, the throughput of RT ser-vices is shown to be equal to N times the through-put of a single channel[8],

T1 = NG1

Nexp

(− G1

N

)= G1 exp

(− G1

N

). (1)

For the access of NRT services, the average num-ber of remaining PACH after RT reservation is

R = N − T1 = N − G1 exp(− G1

N

). (2)

According to the above description, the total ar-rival rate of slot i involves not only aggregated ar-rivals in time domain at slot i, but also the back-logged arrivals owing to frequency domain backoffcaused by collision at slot i − 1. Then we have

G2(i) = Gnew + pαG2(i − 1). (3)

Here, p represents user collision probability atslot i − 1. Factor α is introduced to indicate theimpact of the value of W on the added arrival rate,

α =

W−1∑i=1

pi

W∑i=1

pi

=1 − pW

1 − pW+1. (4)

The value of α is interpreted as the ratio of fre-quency domain backoff at slot i to the number ofcollisions at slot i − 1. Assuming that each access

2408 JIANG F et al. Sci China Ser F-Inf Sci | Dec. 2009 | vol. 52 | no. 12 | 2406-2414

slot is independent, by omitting the slot index, wehave

G2 =Gnew

1 − p 1−pW

1−pW+1

. (5)

Since the users and RNs are assumed to be dis-tributed uniformly in the cell, the total of the newand backlogged arrivals of NRT services in one ac-cess slot is uniformly dispersed in the coverage ofeach RN. Thus, the expectation of NRT servicesbelonging to each RN is

E(Gi) =G2

r.

i∈[1,r]

(6)

The throughput of the NRT services at each RNis then calculated as

T2 = RE(Gi)

Rexp

(− E(Gi)

R

)

= E(Gi) exp(− E(Gi)

R

)

=Gnew(1 − pW+1)

r(1 − p)

· exp(− Gnew

rR

(1 − pW+1

1 − p

)). (7)

By (7), user collision probability p has direct im-pact on the throughput; thus it is essential to ob-tain its value. According to its definition, we have

p =E{collision}

E{collision} + E{success} , (8)

E{collision} =∑∞

k=2 k (G2/R)k

k!exp(−G2

R) =

G2/R(1− exp(−G2/R)), which can be interpretedas follows: when two or more packets access thesame PACH channel, a collision is bound to hap-pen. Meanwhile, the user with NRT service cansuccessfully access the channel if only one packetarrives at a certain PACH channel, expressed as

E{success} =G2

Rexp

(− G2

R

). (9)

By substituting the above expectations into (8),p is now denoted as

p = 1 − exp(− G2

R

). (10)

The throughput expression in (7) is a functionof variables G2 and p, whereas the two parametersinfluence each other. Therefore, we obtain p, G2

and T2 in a recursive manner.

The access delay of the NRT services, on theother hand, heavily depends on how many timesof collision happen before a user successfully ac-cesses the channel. However, since the value of W

is dynamically updated by each RN, it might beapter to obtain the probability distribution of theaccess delay from p. More specifically, the proba-bility that access delay is smaller than or equal toW + 1 slots is given by

pr{access delay � W + 1}

= (1 − p)W∑i=0

pi = 1 − pW+1. (11)

3.2 Adaptive value of W

One of the remarkable features of the AMRASscheme is that the RN will adaptively determinethe maximum allowed frequency backoff windowW at the beginning of each slot; the detailed pro-cedure is presented in this subsection.

Denote the initial value of W at the beginning ofslot i by Wi. After a round of NRT random access,the RN will calculate the value of p at the end ofslot i. By jointly consider the combined new andtime domain backlogged arrivals during slot i to-gether with the number of remaining PACH chan-nels, the RN is able to estimate the optimal valueof W at slot i + 1. To this end, the RN executesthe following five steps.

Step 1. RN compares the values of R andGnew in slot i+1 with those in slot i, consequentlyadopts different strategies:

If R(i + 1) < R(i) and Gnew(i + 1) > Gnew(i),turn to step 2.

If R(i + 1) > R(i) and Gnew(i + 1) < Gnew(i), goto step 4;

For other cases, first execute step 2, then skip tostep 4.

Step 2. If Wi − 1 � 0, update Wi+1 = Wi − 1;otherwise, Wi+1 = 0 and exit.

Step 3. If T2(Wi+1) > T2(Wi), go to step 2;otherwise set Wi+1 = Wi+1 + 1 and exit.

Step 4. If Wi + 1 � R/2, update Wi+1 =Wi + 1; else Wi+1 = Wi and exit.

Step 5. If T2(Wi+1) > T2(Wi), go to step 4;otherwise set Wi+1 = Wi+1 − 1 and exit.


Through implementing the above steps, the RNcan find a proper value of W at each access pe-riod. The core concept of the above algorithm isthe “throughput maximization” in searching actionof step 3 and step 5, which aims at finding the exactbackoff window leading to maximized throughput.This is archived according to the new arrival rateas well as the number of remaining PACH channels.The stopping criterion is that either the optimal W

is archived or the boundary conditions are reached(e.g. W equals zero or R/2, which is regarded asthe lower or upper bound initially set by each RN).

After the RN decides the optimal value of W forslot i+1, it should send this information to all theusers trying to access this RN. It is worth notingthat this information can be piggybacked in thebroadcast message, which is sent by RN announc-ing the available random access channels at thebeginning of this slot. Therefore, without incur-ring any additional signaling overheads, each userwith NRT service can adjust its values of W in adistributed way according to the received informa-tion.

3.3 Analytical performances with inter-ference considered

The performances of the former subsection are ac-quired with the hypothesis that perfect power con-trol is adopted at RNs. In this subsection, withouttaking power control into consideration, the im-pact of interference induced by full channel sharingamong RNs is carefully investigated.

Specifically, through service differentiation, RNswill share the same resources left after RT reser-vation. However, if a perfect scheduling algorithmis adopted, the intra-cell interference caused by re-sources reuse can be considerably avoided. On theother hand, the inter-cell interference (ICI) is ac-tually the main constraint on better cell capacity.Consider the scenario where some arrivals gener-ated by a certain RN may influence the access re-quests of neighboring RNs located in other cells.To clarify the performance analysis, let M denotethe number of interfering RNs, and β represent theaverage ratio of interference range to RNs cover-age. Then β ∈[0,1] which can be interpreted as fol-lows: β approaches to zero if the interference range

shrinks and tends to one if interference range ex-pands. Therefore, the arrival rate induced by ar-rivals from neighboring RNs is now expressed asβMG2/r. When users are uniformly distributed,the combined total arrival rate of NRT services isG2(1+βM)/r. Thus, with interference considered,the throughput of NRT access packets at each RNis

T I2 =

Gnew(1 + βM)(1 − pW+1)r(1 − p)

· exp(− Gnew(1 + βM)

rR

(1 − pW+1

1 − p

)). (12)

Compared with (7), the equation displayed in(12) illustrated the great impact of interference onthroughput owing to full channel sharing. In or-der to suppress the interference referred to above,the concept of fractional frequency reuse (FFR)scheme, which is widely employed in LTE system,can be applied to RN based networks as a pos-sible ICI mitigation technique. A straightforwardexample of the two-hop relay based framework em-ploying FFR is illustrated in Figure 1.

Figure 1 The structure of fractional frequency reuse scheme.

As depicted in this figure, in each cell all non-overlapped PACH channels are divided into twoparts: one part is named minor sub-channel groupwhile the other part is called major sub-channelgroup. In order to coordinate server interferencecaused by frequency multiplexing at boarder re-gion, the minor sub-channel group is specified tobe used only in the inner coverage of the RNs andcan be multiplexed for each RN only with restricted


transmission power. The major sub-channel group,on the other hand, can be used within the wholecoverage of the RNs and should be orthogonal be-tween neighboring RNs to mitigate most of the in-terference.

Under this structure, the proposed AMRASstrategy works as follows: users with NRT serviceslying in the inner coverage of RNs can send theiraccess packets through the minor sub-channels,while other users which are located at the edge ofthe RNs, can send their access information throughthe major sub-channels. With the same assump-tion that factor β represents the ratio of interfer-ence range to RNs coverage, it can be inferred thatwhen FFR scheme is adopted, the arrival rate ofNRT services, which are in the vicinity of the RN,can be calculated as (1 − β)G2/r, whereas the ar-rival rate of other NRT services, which are at theedge of the RN, is represented as βG2/r. Accord-ingly, the total NRT services arrival rate at eachRN is given by

GFFR2 =

G2((1 − β) + βM)r

=Gnew(1 + βM − β)(1 − pW+1)

r(1 − p). (13)

Therefore, under FFR scheme, the throughputof NRT access packets at each RN is expressed as

T FFR2 =

Gnew(1 − β + βM)(1 − pW+1)r(1 − p)

exp(− Gnew(1 − β + βM)

rR

(1 − pW+1

1 − p

)). (14)

Accordingly, the user collision probability is up-dated as

pFFR = 1−

exp(− Gnew(1 − β + βM)

rR

(1 − pW+1

1 − p

)). (15)

Finally, the probability that access delay issmaller than or equal to W + 1 is

pr{access delay � W + 1}= 1 −

(1 − exp

(− Gnew(1 − β + βM)

rR

·(

1 − pW+1

1 − p

)))W+1

. (16)

4 Numerical results

The access performances of the proposed AMRASfor multi-channel relaying networks are provided inthis section. In numerical evaluations, the scenar-ios where 2, 4 and 6 RNs are deployed in a cellare considered. BS is located at the center of thecell, while the RNs are distributed uniformly in thecell. All users are supposed to be evenly distributedwithin the whole cell with integrated service for ac-cess. Besides, the ratio of the voice users to thatof data users is 1:2 and the total number of RACHchannels is set at 20. Moreover, it is assumed thatchannel condition is not considered in the simula-tion and the packet access failure is only due tocollision.

The throughput in the figures is measured as thesuccessful accessed requests per access slot and thedelay performance is given by probabilities. Fur-thermore, the collision probability is calculated bythe ratio of the unsuccessful transmitted packetsto the total transmitted requests in the system.

Figure 2 shows the throughput curves as a func-tion of number of NRT users. To make a com-parison, the performances of conventional slottedAloha as well as the scheme without adaptive fre-quency backoff window is also displayed. As usernumber increases, AMRAS achieves better accessthroughput than that of slotted Aloha. In addition,with the increasing number of RNs in the cell, thethroughput performs much better. As can be ob-served, with adaptive value of W , more frequencydomain backoffs contribute to the total arrival rate.So the maximum throughput is obtained at lowerarrival rate. According to the proposed updatingprocedure, W firstly approaches to the R/2 underlight load, and then gradually decreases with theincrease of arrival rate, and finally it will convergeto zero. This phenomenon is demonstrated in Fig-ure 2 that under light load AMRAS overlaps withthe curve where W equals R/2; while under heavyload, AMRAS coincides with the situation whenW is always equal zero.

Figure 3 plots the user collision probability ac-cording to different numbers of RNs. As shownin the figure, the collision probability of NRT ser-vices with the proposed scheme is much lower than


that of the slotted Aloha as well as non-adaptationscheme. And it keeps descending owing to theincreasing RNs. Again it is observed that withadaptive value of W , user collision probability ap-proaches to the curve where W equals R/2 underlight load; while under heavy load, user collisionprobability tends to the situation when W is al-ways equal zero. Although collision probability in-creases with adaptive value of W , as illustratedin Figure 2, the throughput performances becomemuch better under normal load.

Figure 2 Throughput versus new arrival rate.

Figure 3 User collision probability versus new arrival rate.

Figure 4 depicts the probability of access de-lay smaller than W + 1 slots according to NRTusers. With the increase of arrival rate, the pro-posed AMRAS adopts a decreasing value of W ;hence the probability of access delay smaller thanW + 1 slots is also decreased. However, under amoderate load, most NRT services adopting the

proposed AMRAS successfully access the PACHchannel within W + 1 slots. While in conventionalslotted Aloha scheme, when an access request fails,it will experience a long time backlog in the futureslots, so the access delay cannot be guaranteed. Inaddition, it is observed that with the increasingnumber of RNs and adaptive value of W , the ac-cess delay is decreased. The reason that the delayprobability of the non-adaptation scheme is higherthan that of AMRAS is owing to the fact that theformer always employs a constant backoff window.

Figure 4 Prob.[access delay � W+1] versus new arrival rate.

Figure 5 shows the ratio of G2 to Gnew as a func-tion of NRT users. During periods of light or nor-mal load, most NRT requests suffering from col-lision will immediately begin a frequency domainbackoff, subsequently contributing to the highervalue of G2. This is verified by the phenomenonshown in the figure that at beginning the ratio ofG2 to Gnew is gradually increasing. However, whenthe system gradually reaches saturation, users withNRT services will accordingly begin a time domainretransmission instead of frequency domain retrial,thus inducing a decrease of G2. Besides, as clearlyshown in the figure, there is an iteration processof G2/Gnew which is in accordance with the chang-ing value of W adopted by each RN at the begin-ning of access period. With the increasing arrivalof NRT users, more users will suffer from randomaccess collisions. According to the proposed AM-RAS scheme, the value of W will gradually becomesmaller so that users can end frequency backoff ear-lier and start time domain retransmission sooner.


This gives the reason why curves for G2/Gnew showsuch an irregularity.

Figure 5 G2/Gnew versus new arrival rate.

In the above assessment, through effective powercontrol and adaptive backoff strategy, the RNs inthe cell share the NRT accesses originally affordedby the BS; thus the access throughput is improvedwith the number of RNs, while the collision prob-ability and access delay are decreased. However,when taking interference into consideration, it isnecessary to evaluate the behavior of the proposedAMRAS strategy under FFR scheme.

The simulation scenario is similar to that in Fig-ure 1 where the BS is placed at the cell center sur-rounded by 6 position fixed RNs. Consequently, fora given RN, the number of interfering RNs is five.Other parameters remain the same as previouslyevaluated.

Figures 6–8 indicate the access throughput, col-lision probability and access delay probability per-formances of the AMRAS based on fractional fre-quency reuse for NRT services, respectively. Fromthose figures, it can be concluded that with in-creased β, the access throughput of the proposedAMRAS is degraded, while the collision probabil-ity and access delay are raised. This is owing to thefact that with the increasing value of β, the inter-ference range of each RN gradually expands. As aresult, the access requests of NRT users intendingto access a certain RN will actually affect the ac-cess process of the neighboring RNs. Fortunately,with the introduction of fractional frequency reusescheme for PACH sub-channel sharing, the inter-

ference yielded by full frequency reuse is effectivelysuppressed, and the throughput, collision ability aswell as access delay performances are all enhanced.

Figure 6 Throughput comparison with/without FFR.

Figure 7 User collision probability comparison with/without

FFR.

Figure 8 Prob.[access delay � W+1] comparison with/with-

out FFR.


5 Conclusions

This paper presents an adaptive multi-channel ran-dom access strategy (AMRAS) for cooperative re-lay based networks with multiple random accesschannels. For the sake of fast and efficient access ofNRT requests, AMRAS adopts an adaptive back-off strategy according to current user arrival rateas well as the number of remaining PACH chan-nels. In the proposed scheme, users with NRT re-quest will directly send their packets into the near-est RN; the RN will then relay the access requeststo the BS in a pre-scheduled manner. Once the ini-

tial access fails, it will retransmit over a differentPACH channel instead of in a different time slot.The RN will adaptively determine the maximumallowed frequency backoff window and broadcastthis information at each access period. Moreover,we also consider the impacts of interference on theproposed AMRAS, and analyze the performance ofan effective sub-channel sharing scheme. Numeri-cal results demonstrate that our scheme achieveshigher throughput, lower collision probability andlower access delay than conventional slotted Alohaas well as non-adaptation case.

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