capacity optimizing channel allocation schemes for multi-service cellular systems

INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMSInt. J. Commun. Syst. 2004; 17:575–590 (DOI: 10.1002/dac.669)

Capacity optimizing channel allocation schemes formulti-service cellular systems

Ming Yangn,y and Peter H. J. Chongz

Network Technology Research Center, School of EEE, Nanyang Technological University, Nanyang Avenue,

Singapore 639798, Singapore

SUMMARY

The trend of the wireless communication system is to provide various types of services such as voice, dataand video etc. Due to the limited radio resources with international agreement, how to achieve theoptimum system capacity becomes a paramount issue. In this paper, we use the idea of channel partitioning(CP) employing different reuse factors to support multiple services that require different signal-to-interference ratios (SIRs) in cellular systems. Two types of services are considered in this paper. Thus, weuse a large reuse factor to support high SIR required service while we use a small reuse factor to supportlow SIR required service. From the system point of view, the average reuse factor becomes smaller and thesystem capacity can be improved. The system performance of CP with fixed channel allocation (FCA)scheme, namely fixed channel partitioning (FCP), is first proposed and analysed using Markov chain in asingle cell model. Then a dynamic channel allocation scheme with CP called dynamic channel partitioningwith interference information (DCP-WI) is proposed and studied in the multiple-cell model by computersimulation. The analysis and simulation results show that our proposed schemes can improve the systemcapacity depending on the traffic load fraction for each service. For equal arrival rate for both services,FCP and DCP-WI provide about 33 and 60% capacity improvement respectively over a conventional FCAsystem using a single reuse factor to support two types of services. Copyright # 2004 John Wiley & Sons,Ltd.

KEY WORDS: dynamic channel allocation; multiple services; channel partitioning and cellular systems

1. INTRODUCTION

With the development of the more advanced technologies, wireless communication systemperforms more than just a voice-provider system. The trend of the wireless communicationsystem is to provide various types of services. One of the major problems in multiple servicessystem is the signal to interference ratio (SIR) problem. For example, the required bit error rate(BER) for speech service is 10�3; while the required BER for circuit- or packet-switched dataservice is 10�6 [1]. This means for data service, we need higher SIR in order to meet the quality

Received 15 October 2003Revised 15 February 2004

Accepted 30 April 2004Copyright # 2004 John Wiley & Sons, Ltd.

yE-mail: [email protected]

nCorrespondence to: Ming Yang, Network Technology Research Center, School of EEE, Nanyang TechnologicalUniversity, Nanyang Avenue, Singapore 639798, Singapore.

zE-mail: [email protected]

of service (QoS) requirements. But for the speech service, we need lower SIR. The limitedspectrum resource is an obstruction to provide good QoS to the multiple services. Thus, efficientresource allocation is needed to support these multiple traffic optimally. The studies to supportthe multiple services are presented in References [2–4]. In References [2, 3], the high-rate-dataservice is split into two or more parts and transmitted independently through different channels.In Reference [4], different kinds of networks are built with each supporting certain kinds ofservices. In these previous studies, a single reuse factor is assumed to support these multipleservices. If a single reuse factor is assumed, normally, the largest one among these services willbe used to support them in order to meet the co-channel interference constraints. Since thesemultiple services may require different reuse factors to cater for the different SIR requirements,using a single (largest) reuse factor to support multiple services may result in the wasting of theavailable radio resources.

In this paper, we use channel partitioning (CP) idea employing different reuse factors tosupport these multiple services requiring different SIRs. Two types of services are studied. Weuse large reuse factor to support high SIR required service, i.e. data service, while use smallreuse factor to support low SIR required service, i.e. voice service. In CP, the total systemchannels are divided into two sets. Each set of the channels supports traffic with lower or higherreuse factor. From the system point of view, the overall reuse factor becomes smaller and thecapacity of the system can be improved. We first introduce and analyse this CP with fixedchannel allocation (FCA) scheme, called fixed channel partitioning (FCP), in a single cell systemmodel. Markov chains are developed to obtain the numerical results. A scaling method isintroduced to deal with different call duration scenario. In order to cater for the short-termtemporal and spatial variation between cells, we apply this CP to a previously proposed channelallocation algorithm DCA-WI [5] in the multiple cell system model called dynamic channelpartitioning with interference information (DCP-WI). Both analysis and simulation resultsshow that FCP and DCP-WI outperform the conventional FCA system, which uses a single(largest) reuse factor to support multiple services.

2. FCP SCHEME

2.1. System model

For simplicity, two types of services: service type1 (S1) and service type2 (S2) are considered inthis study. We assume that the reuse factor, N1; of S1 is smaller than the reuse factor, N2; of S2:Thus, S1 is low SIR required service and S2 is high SIR required service. The fraction of arrivalrates for S1 and S2 are assumed to be g1 and g2; respectively. Calls are assumed to be uniformlydistributed over the service area and arrive according to a Poisson process with a per cell arrivalrate of l ¼ l1 þ l2; where l1 and l2 are per cell arrival rates for S1 and S2 calls respectively, i.e.li ¼ gi � l; for i ¼ 1 or 2. An arriving call that cannot be assigned a channel is blocked anddeparts the system. Call duration time is exponentially distributed for S1 and S2 calls withmeans of 1=m1 and 1=m2: The offered traffic (in Erlangs) to S1 and S2 calls of a cell is defined asr1 ¼ l1=m1 and r2 ¼ l2=m2: Then, the total traffic load per cell is r ¼ r1 þ r2: Let C1 and C2 bethe number of channels supporting S1 and S2 calls respectively in each cell and CFCP ¼ C1 þ C2

be the total number of channels per cell. If the total number of system channels is m; it mustsatisfy N1C1 þN2C24m:

Copyright # 2004 John Wiley & Sons, Ltd. Int. J. Commun. Syst. 2004; 17:575–590

M. YANG AND P. H. J. CHONG576

Since FCP uses two reuse factors instead of the highest reuse factor for channel allocation asused in a conventional FCA, the average reuse factor of FCP is smaller. Thus, CFCP is largerthan the number, CFCA; of channel per cell in FCA, i.e. CFCA ¼ m=N2: This will be shown inSection 4.

2.2. Performance analysis of FCP

In our proposed FCP, we allow S1 calls, which are low SIR required services, to use C2

channels, which are large reuse factor channels. This is called overflow technique. A new S1 callis first assigned to an unused C1 channel. If all C1 channels are busy, it will be assigned anunused C2 channel. If no such unused channel is found, the S1 call is blocked. New S2 calls useonly free C2 channels. If no free C2 channels are found, the S2 calls are blocked. The reverseoverflow, i.e. S2 calls to use C1 channels, is not allowed due to co-channel interferenceconstraints. A two-dimensional Markov chain as shown in Figure 1 can represent this two-traffic FCP system for m1 ¼ m2 ¼ m: Each node in the figure represents a state ðx; yÞ; where x; yare the numbers of C1 and C2 channels occupied respectively. Thus, the set of allowable states isgiven by S ¼ fðx; yÞ j 04x4C1; 04y4C2g:

An assignment of a S1 call to a free C1 channel is represented by a transition from the currentnode to its right node with a transition rate of l1: Similarly, an arriving S2 call to a free C2 isrepresented by a transition from the current node to the up node with a transition rate l2:Because of the overflow technique when all C1 channels are busy and S1 call uses C2 channel, atransition from the rightmost nodes, i.e. from nodes ðC1; 0Þ to ðC1;C2 � 1Þ; to the up node with atransition rate of l1 is needed. Thus, we can see from Figure 1, the transition rates from nodesðC1; 0Þ to ðC1;C2 � 1Þ to the up nodes are therefore l1 þ l2: The departure of a call using C1 orC2 channel in the right-most column is represented by transitions from the current node to theleft and down node with transition rates of xm and ym; respectively.

Figure 1. Markov chain of the FCP.


CAPACITY OPTIMIZING CHANNEL ALLOCATION SCHEMES FOR MSCS 577

If m1=m2; Figure 1 cannot be used directly to model the FCP because the downwardrightmost transition rate is no long ym; but in terms of m1 and m2: Thus, a scaling method is used.First, we assume the service rate of S2 to be equal to the service rate of S1: Then, we need toscale the arrival rate of S2; i.e.

m2 ¼ m1

l2 ¼m1m2

� �l2

ð1Þ

Then, we replace l2 by l2 and use the same Markov chain to represent the system. The scalingmethod in (1) is to ensure that the traffic load for S2 remain the same value, i.e.

r2 ¼l2m2

¼l2m2

The Markov chain in Figure 1 can be solved numerically [6] to obtain the steady-stateprobabilities, pðx; yÞ: From Figure 1, it can be seen that the call blocking probability, PB;1 for S1

is when no C1 or C2 channel is available, i.e.

PB;1 ¼ pðC1;C2Þ ð2Þ

The call blocking probability, PB;2; for S2 is when no C2 channel is available, i.e.

PB;2 ¼XC1

x1¼0

pðx1;C2Þ ð3Þ

We can also get from (2) and (3) that the blocking probability of S1 is always lower than that ofS2: The average call blocking probability, PB;ave; for FCP is given by

PB;ave ¼ g1PB;1 þ g2PB;2 ð4Þ

2.3. Performance analysis of FCP with switching

In the previous channel allocation procedure, we have such situation that some C1 channels arefree (because of the departure of the S1 calls) and all the C2 are busy (some C2 channels might beborrowed by S1 calls). If a new S2 call comes into the system, the S2 call is blocked because thereis no free C2 channel for S2 call to be used although there are some free C1 channels. So weintroduce switching technique to settle this problem. Switching technique can ensure that S1

calls use their own C1 channels whenever they are available. Thus, it can reduce the blockingprobability for the S2 calls.

With switching, when a S1 call using C1 channel completes its service and releases a C1

channel, another on-going S1 call using C2 channel, if any, will release its currently used C2

channel and switch to that just released C1 channel. Such FCP with switching can be representedby a standard two-dimensional Markov chain as shown in Figure 2. At this time, the states, aand b; represent the numbers of S1 and S2 calls existing in the system, which are different from xand y that we have mentioned in Section B: And the allowable states are given by S ¼fða; bÞ j 04a4C; b ¼ minfC � a;C2gg: The procedure of assigning or releasing of a channel to acall is same with the previous Markov chain. Except that the overflow and switching arerepresented by the right part of the Markov chain for all states a5C1 þ 1: For example, the



state, ðC1 þ 1; 2Þ; means that all the C1 channels are busy and three C2 channels are used withone channel borrowed by S1 call.

This standard two-dimensional Markov chain can be solved numerically by a closed productform solution [7] and the steady-state probability for each state is given by

Pða; bÞ ¼ra1

a!rb2

b!Pðx;yÞ2S

rx1

x!ry2

y!

ð5Þ

So, the blocking probability, P1; of S1 is the states that all C1 and C2 channels are busy and isgiven by

P1 ¼X

fða;bÞjC�C24a4C;b¼C�ag

Pða; bÞ ð6Þ

and the blocking probability, P2; of S2 is the states that all C2 channels are busy and is given by

P2 ¼X

fða;bÞj04a4C;b¼minfC�a;C2gg

Pða; bÞ ð7Þ

And the average call blocking probability, PB;ave; for FCP with switching is given by

PB;ave ¼ g1P1 þ g2P2 ð8Þ

3. DCP-WI SCHEME

In cellular mobile systems, the traffic load distribution among different cells may be different.Thus, conventional fixed channel allocation (FCA) is not adaptive enough to cater for the short-term temporal and spatial variations of traffic load among cells. Dynamic channel allocation(DCA) on the other hand provides a more flexible way to use the limited radio resource. A

Figure 2. Markov chain of the FCP with switching.



network-based DCA scheme called dynamic channel allocation with interference information(DCA-WI) was proposed and studied in Reference [5]. In DCA-WI, each cell uses aninterference information table (IIT), which contains sufficient information about the status ofchannels in each interfering cell, to allocate channels to users. DCA-WI tries to manage thechannel allocation between cells in a proper way so that each allocation of the channel causesleast interference to the neighboring cells. We apply the CP algorithm to this DCA-WI schemecalled dynamic channel partitioning with interference information (DCP-WI).

3.1. IIT

In DCP-WI, each cell has two IITs (for S1 and S2 calls respectively) that contain sufficientinformation of channel status of its own and interference cells. A certain numbers of channels,C1 and C2; are allocated for S1 and S2 calls respectively, depending on the traffic load. Forexample, as shown in Tables I and II, there are 28 channels allocated as C1 channels and 182channels are allocated as C2 channels, assuming m ¼ 210:

In Tables I and II, the first column indicates the own cell (O CELL) and all its interferencecells (I CELL). As shown in Figure 3 for cell 25, if we assume the reuse factor of N1 and N2 are 4and 7, respectively; there are 12 and 18 interference cells in Tables I and II, respectively. Theother columns stand for the channels status corresponding for each channel of a particular cell.A letter U in Tables I and II in [I CELL or O CELL, channel j] box indicates that this channel isa used channel. For example, in Table II, the cell 25 uses channels 32 and 209 and the cell 39uses channel 31. A letter U 0 in Table II indicates that this channel is a channel borrowed by S1

call such that overflow is employed in DCP-WI. For example, in Table II, channel 29 isborrowed by a S1 call in cell 25. A letter L in [I CELL, channel j] box indicates that this channelis used and locked by an I CELL’s interference cell, say cell X ; which is not the interference cellof O CELL. This means that channel j is a LOCKED CHANNEL in I CELL and it is notallocated to use in that I CELL. For example, in Table I, channel 2 is locked in cell 12 becauseone of cell 12’s interference cell, say cell 5 (refer to Figure 3), which is not an I CELL of cell 25,is using channel 2. Thus, cell 12 cannot use channel 2 due to co-channel interference constraints,but cell 25 can still use channel 2. An empty box in [O CELL, channel j] box indicates that thischannel is either a FREE CHANNEL (if there is no U or U 0 in this column) or a LOCKEDCHANNEL (if at least one U or U 0 is in this column). For example, in Table II, channel 30 is aFREE CHANNEL in cell 25 and channel 33 is a LOCKED CHANNEL, which is locked by cell

Table I. IIT of cell 25 for S1:

Channel no. for S1

Cell no. 1 2 3 4 5 . . . 27 28

25 U12 L L L 3L17 L L L18 L L19 U L L L L...

39 U



19. A LOCKED CHANNEL here means that one or more I CELL(s) of O CELL currentlyuse(s) this channel.

3.2. Channel assignment and reassignment

The channel allocation of DCP-WI tries to minimize the effect of the assignment on channelavailability in all the interfering cells of O CELL. The idea is to allocate a channel that has beenlocked by the maximum number of I CELLs. For example, if a new S1 call arrives in cell 25,

Table II. IIT of cell 25 for S2:

Channel no. for S2

Cell no. 29 30 31 32 33 . . . 209 210

25 U 0 U U...

..

.

19 2L U 0 L...

38 L39 U

12

2322

2120

1918

1716

15

1413

1211

109

8

76

54

3

4948

4746

4544

43

4241

4039

3837

36

3534

3332

3130

29

2827

2625

24

Figure 3. System model for 49 cells with two reuse factors.



refer to Table I, channel 5 is preferred to be used because assigning channel 5 to thisnew call will affect 8 I CELLs and these 8 I CELLs cannot use channel 5. If otherchannel is assigned, more I CELLs will be affected. For example, the assigning of channel28 will affect 10 I CELLs, which cannot use channel 28. Information about whether achannel j is locked or not in I CELL of O CELL is provided in the O CELL’s IIT. Achannel j is locked if there is at least an L in channel j’s column. A channel j with thesmallest value of the cost functions, MINfCð jÞ or C0ð jÞg; as in (9) and (10), is allocatedto the new arrival call in O CELL to use. If that new call cannot get a channel, it isblocked.

The cost functions, Cð jÞ or C0ð jÞ; for channel assignment and reassignment can be used forboth S1 and S2 calls. The Cð jÞ for channel assignment is for all free channels in O CELL and isgiven as

Cð jÞ ¼ NðAÞ � LðA; jÞ ð9Þ

where NðAÞ is the number of interference cells of O CELL, say cell A: In our assumption, NðAÞis 12 for S1 calls using C1 channels, while NðAÞ is 18 for calls (S1 or S2) using C2 channels.LðA; jÞ is the number of locked cells of O CELL (cell A) for channel j; e.g. Lð25; 4Þ is 2 as shownin Table I. We can see from the function that NðAÞ is pre-defined constant in the system. If weget the maximum value of LðA; jÞ for a channel j; then we can achieve the minimum value ofCð jÞ: To give an extreme case for an example, when channel j in all I CELLs of O CELL arelocked, i.e. LðA; jÞ ¼ NðAÞ; then O CELL can use this channel freely without causing anydisturbance to its interference cells. Because all these I CELLs are locked and cannot use thischannel j:

A single channel reassignment is considered here to further improve the system capacity. TheC0ð jÞ for channel reassignment is for all locked channels with a single locked cell. A channel,channel j; is a locked channel with a single locked cell in O CELL if there is only one U or U 0 inan I CELL in channel j’s column. For example, refer to Table II, channels 31 and 33 are lockedchannel with a single locked cell in cell 25. When allocating a locked channel j to a new call in OCELL, we may reassign the call using that channel j in I CELL to other channel i in I CELL inorder to free channel j in O CELL. The cost function for the single channel reassignment is givenby

C0ð jÞ ¼ ½NðAÞ � LðA; jÞ� þ ½LðB; jÞ � LðB; iÞ� ð10Þ

where LðB; jÞ is the number of locked cells of the I CELL, cell B, of O CELL for channel j:LðB; iÞ is the number of locked cells of the I CELL, cell B, of O CELL for channel i: The lockedcell number of LðB; jÞ and LðB; iÞ are obtained from cell B’s IIT. The purpose of (10) is tominimize the impact on the interference cells of switching the on-going call using channel j tochannel i:

The costs for all free channels and locked channels with a single locked cell are obtained usingCð jÞ and C0ð jÞ; respectively. A channel with the lowest cost will be allocated to the new arrivalcall.

3.3. The priority of channel for assignment

From the cost functions with (9) and (10), we choose the channel with smallest cost value to beassigned to the new service call. When there is more than one channel with the same smallest



cost function value, the selection order of the channel is based on the following rules with thefirst one having highest priority:

(1) A channel with a larger number of locked cells has higher priority. For example, inTable I, channel 5 with 4 locked cells, has higher priority than channel 27, with only 1locked cell.

(2) A free channel has higher priority, e.g. in Table I, channel 27 has higher priority thanchannel 3.

(3) If several channels have same number of locked cells, a lower-numbered channel hashigher priority, e.g. in Table I, channel 4 has higher priority than channel 28.

(4) If several single reassignment channels have the same number of locked cells, a lower-numbered channel has higher priority, e.g. in Table II, channel 31 has higher prioritythan channel 33.

3.4. Cell updating

After assigning or releasing of a channel, the IITs should be updated to the changing status ofthe channel. When a BS attempts to allocate channel j to its O CELL, the updating procedurefollows four steps:

(1) A letter U (U 0 if the channel is borrowed by a S1 call) should be inserted in the [O CELL,channel j] box in O CELL’s IIT.

(2) O CELL informs all its I CELLs that a letter U or U 0 should be inserted to the box of [OCELL, channel j] in I CELL’s IIT.

(3) All the I CELLs inform all of their interference cells, say cell X ; which is not theinterference cell of O CELL, that a letter L should be added to the box of [I CELL,channel j] in cell X ’s IIT.

(4) Then, each cell X sends the latest number of locked cells of channel j to all itsinterference cells.

The updating procedure for releasing channel is done in the similar way as above except thatthe ‘inserting’ a letter U or U 0 should be replaced by ‘removing’. The ‘adding’ of a letter Lshould be replaced by ‘subtracting’.

3.5. Other assignment technique}rearrangement

Other assignment techniques such as overflow, switching and rearrangement are applied toDCP-WI in order to enhance the performance. Overflow and switching have been introduced inSection 2. In this section, we will introduce the technique of rearrangement.

In DCP-WI, an on-going call process may be rearranged to a released channel to minimizethe effect on the interference cells during its service. Many algorithms have been proposed inthis area [8, 9]. In DCP-WI scheme, the rearrangement of the channel is also based on theIIT’s information. If a channel j is released in O CELL, an on-going call in O CELL using achannel i with the least number of locked cells will switch to that channel j provided that thenumber of locked cells in channel j is higher than that in channel i: If more than one channel hasthe same least number of locked cells, the highest numbered channel will perform therearrangement.



Always, the rearrangement will work combined with switching algorithm. The differencebetween switching and rearrangement is that switching should be performed between two typesof channels for S1 calls only while rearrangement is performed between same traffic channels forboth services. When a traffic1 channel is released, switching will first be performed. Then, therearrangement will be followed. In our proposed DCP-WI algorithm, we consider overflow,switching and rearrangement at the same time.

4. NUMERICAL RESULTS AND DISCUSSIONS

For FCP, we consider a single cell as a reference cell to achieve the system capacity. Butfor DCP-WI, we consider a multiple cells environment of 49 cells, as shown in Figure 3,to represent the practical system. In order to avoid boundary effect, wrap-around techniqueis used in the multiple cells. That is, in Figure 3, the left most cells are deemed connectingwith rightmost cells. So are the bottom and upper cells. The total number of channel, m ¼ 210;are studied to support two types of services. The reuse factor in FCP and DCP-WI areassumed to be 4 and 7 for S1 and S2 calls. For both FCA and DCA-WI, a single reuse factor of7 is used to support both services. Therefore, CFCA is 30 per cell and the total system channelfor DCA-WI is 210. The mean call durations, 1=m1 and 1=m2 for S1 and S2; are assumed tobe 100 and 50 s: The S1 service can be considered as a traditional voice call that requireslower reuse factor and longer call duration time. The S2 service can be considered asa data service. The traffic performance for the connection blocking probability, Pb; isaimed at 1% for FCP, DCP-WI, DCA-WI and FCA. Different channel combinations,CðC1;C2Þ; for FCP and DCP-WI are simulated to achieve the best performance. Rememberthat C1 and C2 for FCP means the number of channels allocated per cell for S1 and S2

calls respectively. For DCP-WI, C1 and C2 means the total number of channels in channelpool for S1 and S2 calls. For all the simulation results, the 95% confidence intervals within�5% of the average values are used. Two different traffic load ratios are to be simulated.The first traffic load ratio, r1:r2; is equal to 8:1, which corresponds to the arrival rate ratio,g1:g2; of 0.8:0.2. This scenario can represent the present mobile communication scenario,which the voice traffic is considered to be the main service in the network [10]. The secondtraffic load ratio is 1:2, which corresponds to the arrival rate ratio of 0.2:0.8. This canrepresent the future mobile communication system in which the data traffic will predominate thenetwork.

Figure 4 shows the results of FCP over FCA under the traffic load ratio, r1:r2; of 1:2,i.e. arrival rate ratio, g1:g2; of 0.2:0.8. As we can see from the figure that under low S1

traffic load ratio, FCP gives a little better performance than FCA. Different channelcombinations, CðC1;C2Þ; have been considered. It is found that in this traffic load ratio,Cð7:26Þ provides the best performance and is about 9% better than FCA at Pb ¼ 0:01: Asmentioned in Section 2, the number, CFCP; of channel per cell in FCP is higher than that, CFCA;in FCA due to the overall smaller reuse factor for FCP. In this case, CFCP ¼ 33 and CFCA ¼ 30:As we increase the S1 traffic load ratio, i.e. r1:r2 ¼ 8:1 and g1:g2 ¼ 0:8:0:2 as shown in Figure 5,FCP provides a significant improvement as compared with FCA. And this improvement of thebest channel combination, Cð35:11Þ; is about 59%. In this case, CFCP ¼ 46: Some simulationresults for FCP are also shown in Figures 4 and 5 and they are matched closely with theanalytical results.



Figure 4. The comparison of FCP and FCA for r1:r2 ¼ 1:2:

Figure 5. The comparison of FCP and FCA for r1:r2 ¼ 8:1:



Figures 6 and 7 show the simulation results of DCP-WI over FCA and DCA-WI in uniformtraffic distribution scenario. Under low S1 traffic load ratio, e.g. r1:r2 ¼ 1:2; DCP-WI providesabout 38 and 8% improvement over FCA and DCA-WI, respectively. But under high S1 traffic

Figure 6. The comparison of DCP-WI over FCA and DCA-WIfor r1:r2 ¼ 1:2 in uniform traffic distribution.

Figure 7. The comparison of DCP-WI over FCA and DCA-WIfor r1:r2 ¼ 8:1 in uniform traffic distribution.



load ratio, i.e. r1:r2 ¼ 8:1; DCP-WI gives about 73 and 36% improvement over FCA andDCA-WI.

Figure 8 shows the improvement of FCP, DCP-WI over FCA under different traffic load ratiobetween S1 and S2 calls. As we can see from the figure, with the increasing of the S1 traffic loadratio, the improvements of FCP and DCP-WI over FCA increase. This is because with theincreasing of S1 traffic load, more channels are allocated to support S1 calls for reuse factorof 4 due to more S1 users. So, the overall reuse factor of the channel usage becomes smallerand the system capacity is improved. In the present communication system, the traffic loadfor voice service (requiring small reuse factor) is higher than that for data service.So this proposed algorithm can work properly in the multiple services situation when r1 > r2:From Figure 8, we can see that even for equal arrival rate between S1 and S2 services,i.e. g1:g2 ¼ 0:5:05 (corresponding to r1:r2 ¼ 2:1), which is the test configuration for UMTS [11],FCP and DCP-WI can provide about 33 and 60% improvement over FCA scheme,respectively. It can also be seen that FCP with switching gives additional 5% improvementover FCP without switching. This shows that the proposed switching technique can provideadditional benefit. Compared with FCP scheme, DCP-WI scheme always outperforms FCP.This shows that dynamic channel allocation scheme can further cater for the traffic variationsbetween cells.

The performance of DCP-WI algorithm in the non-uniform traffic distribution scenario isstudied. The non-uniform distribution model in [12] is used in the simulation. Figures 9 and 10show the simulation results of DCP-WI over DCA-WI and FCA algorithm under the trafficload ratio of 1:2 and 8:1, respectively. From the figures we can find that the conclusion of DCP-WI algorithm over DCA-WI algorithm is same as we get in the fixed cellular system model. That

Figure 8. The improvement of FCP (with and without switching),DCP-WI over FCA under different traffic load ratios.



is with the increasing S1 traffic load ratio, the improvement of DCP-WI over DCA-WI is alsoincreasing. The improvements with the best channel combination of DCP-WI over DCA-WIunder these two traffic scenarios are 9 and 33%. But as compared with FCA algorithm, DCP-

Figure 9. The comparison of DCP-WI over FCA and DCA-WIfor r1:r2 ¼ 1:2 in non-uniform traffic distribution.

Figure 10. The comparison of DCP-WI over FCA and DCA-WIfor r1:r2 ¼ 8:1 in non-uniform traffic distribution.



WI can always provide better improvement. The improvement is 98 and 143% in these twotraffic scenarios. In conclusion, DCP-WI is able to cater for the non-uniform distributionenvironment.

5. CONCLUSION AND FUTURE WORK

This paper proposes an idea of channel partitioning (CP) employing different reuse factorsto support multiple services requiring different SIRs. The analysis of the proposed idea ofCP is first introduced with fixed channel allocation scheme. Then, the applying of this CPwith a previously proposed dynamic channel allocation scheme is followed. Twotypes of services are considered in this paper. The results under both uniform and non-uniformtraffic distribution scenarios show that our proposed algorithms can improve thesystem capacity depending on the traffic load ratio between services. With increasingtraffic load for service requiring small reuse factor, the improvement of the proposed schemesover other channel allocation schemes using a single reuse factor increases. For equalarrival rate for both services, FCP and DCP-WI provide about 33 and 60% capacityimprovement respectively over a conventional FCA system using a single reuse factor to supporttwo types of services. The disadvantage of the current schemes is that the best channelcombination (which can provide the best system performance) depends on traffic load ratio. Inother words, different traffic load ratio requires different best channel combination. But it is notadaptive enough because the network traffic load ratio may change from time to time. So ourfuture work will focus on another channel allocation scheme that can flexibly allocate thechannels to meet the network variation such that no pre-allocation of channels to each service isrequired.

REFERENCES

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AUTHORS’ BIOGRAPHIES

Ming Yang was born in Shenyang, China, on October 18, 1978. He received the BSdegree in Information engineering (English intensive) from Dalian University ofTechnology, China, in 2002. Since October 2002, he has been pursuing his PhDdegree at the School of Electrical and Electronic Engineering, Nanyang Technolo-gical University, Singapore. His research interests include handoff, channelallocation, and radio resource management for present and future mobilecommunication systems.

Peter H. J. Chong was born in Hong Kong, China, on June 4, 1970. He received theBEng (with distinction) in electrical engineering from the Technical University ofNova Scotia (currently Dalhousie University), Halifax, NS, Canada, in 1993, and theMASc. and PhD degrees in electrical engineering from the University of BritishColumbia, Vancouver, BC, Canada, in 1996 and 2000, respectively. Between July2000 and January 2001, he worked with Advanced Networks Division at AgilentTechnologies Canada Inc., Vancouver, BC, Canada. Between February 2001 andMay 2002, he was a Research Engineer in the Radio Communications Laboratory atNokia Research Center, Helsinki, Finland, and was involved in research onWCDMA and standardization. Since May 2002, he has been with the School ofElectrical and Electronic Engineering, Nanyang Technological University, Singa-pore, as an Assistant Professor. His research interests are in the areas of wireless and

mobile communications systems including channel assignment schemes, radio resource management,multiple access, and mobile ad hoc networks.



capacity optimizing channel allocation schemes for multi-service cellular systems

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