INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS Int. J. Commun. Syst. 2004; 17:575–590 (DOI: 10.1002/dac.669)
Capacity optimizing channel allocation schemes for multi-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, data and video etc. Due to the limited radio resources with international agreement, how to achieve the optimum 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-tointerference ratios (SIRs) in cellular systems. Two types of services are considered in this paper. Thus, we use a large reuse factor to support high SIR required service while we use a small reuse factor to support low SIR required service. From the system point of view, the average reuse factor becomes smaller and the system 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 a single cell model. Then a dynamic channel allocation scheme with CP called dynamic channel partitioning with interference information (DCP-WI) is proposed and studied in the multiple-cell model by computer simulation. The analysis and simulation results show that our proposed schemes can improve the system capacity 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 FCA system 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 system performs more than just a voice-provider system. The trend of the wireless communication system is to provide various types of services. One of the major problems in multiple services system is the signal to interference ratio (SIR) problem. For example, the required bit error rate (BER) for speech service is 103 ; while the required BER for circuit- or packet-switched data service is 106 [1]. This means for data service, we need higher SIR in order to meet the quality
n
Correspondence to: Ming Yang, Network Technology Research Center, School of EEE, Nanyang Technological University, Nanyang Avenue, Singapore 639798, Singapore. E-mail:
[email protected] z E-mail:
[email protected] y
Copyright # 2004 John Wiley & Sons, Ltd.
Received 15 October 2003 Revised 15 February 2004 Accepted 30 April 2004
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M. YANG AND P. H. J. CHONG
of service (QoS) requirements. But for the speech service, we need lower SIR. The limited spectrum resource is an obstruction to provide good QoS to the multiple services. Thus, efficient resource allocation is needed to support these multiple traffic optimally. The studies to support the multiple services are presented in References [2–4]. In References [2, 3], the high-rate-data service 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 of services. In these previous studies, a single reuse factor is assumed to support these multiple services. If a single reuse factor is assumed, normally, the largest one among these services will be used to support them in order to meet the co-channel interference constraints. Since these multiple 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 the available radio resources. In this paper, we use channel partitioning (CP) idea employing different reuse factors to support these multiple services requiring different SIRs. Two types of services are studied. We use large reuse factor to support high SIR required service, i.e. data service, while use small reuse factor to support low SIR required service, i.e. voice service. In CP, the total system channels are divided into two sets. Each set of the channels supports traffic with lower or higher reuse factor. From the system point of view, the overall reuse factor becomes smaller and the capacity of the system can be improved. We first introduce and analyse this CP with fixed channel allocation (FCA) scheme, called fixed channel partitioning (FCP), in a single cell system model. Markov chains are developed to obtain the numerical results. A scaling method is introduced to deal with different call duration scenario. In order to cater for the short-term temporal and spatial variation between cells, we apply this CP to a previously proposed channel allocation algorithm DCA-WI [5] in the multiple cell system model called dynamic channel partitioning with interference information (DCP-WI). Both analysis and simulation results show 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 in this 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 arrival rates for S1 and S2 are assumed to be g1 and g2 ; respectively. Calls are assumed to be uniformly distributed over the service area and arrive according to a Poisson process with a per cell arrival rate 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 and departs the system. Call duration time is exponentially distributed for S1 and S2 calls with means of 1=m1 and 1=m2 : The offered traffic (in Erlangs) to S1 and S2 calls of a cell is defined as r1 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 be the 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 must satisfy N1 C1 þ N2 C2 4m: Copyright # 2004 John Wiley & Sons, Ltd.
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Since FCP uses two reuse factors instead of the highest reuse factor for channel allocation as used in a conventional FCA, the average reuse factor of FCP is smaller. Thus, CFCP is larger than the number, CFCA ; of channel per cell in FCA, i.e. CFCA ¼ m=N2 : This will be shown in Section 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 call is first assigned to an unused C1 channel. If all C1 channels are busy, it will be assigned an unused C2 channel. If no such unused channel is found, the S1 call is blocked. New S2 calls use only free C2 channels. If no free C2 channels are found, the S2 calls are blocked. The reverse overflow, i.e. S2 calls to use C1 channels, is not allowed due to co-channel interference constraints. A two-dimensional Markov chain as shown in Figure 1 can represent this twotraffic FCP system for m1 ¼ m2 ¼ m: Each node in the figure represents a state ðx; yÞ; where x; y are the numbers of C1 and C2 channels occupied respectively. Thus, the set of allowable states is given by S ¼ fðx; yÞ j 04x4C1 ; 04y4C2 g: An assignment of a S1 call to a free C1 channel is represented by a transition from the current node to its right node with a transition rate of l1 : Similarly, an arriving S2 call to a free C2 is represented 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, a transition from the rightmost nodes, i.e. from nodes ðC1 ; 0Þ to ðC1 ; C2 1Þ; to the up node with a transition rate of l1 is needed. Thus, we can see from Figure 1, the transition rates from nodes ðC1 ; 0Þ to ðC1 ; C2 1Þ to the up nodes are therefore l1 þ l2 : The departure of a call using C1 or C2 channel in the right-most column is represented by transitions from the current node to the left and down node with transition rates of xm and ym; respectively.
Figure 1. Markov chain of the FCP. Copyright # 2004 John Wiley & Sons, Ltd.
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If m1 =m2 ; Figure 1 cannot be used directly to model the FCP because the downward rightmost 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 to scale the arrival rate of S2 ; i.e. m2 ¼ m1 m1 l2 ¼ l2 m2
ð1Þ
Then, we replace l2 by l2 and use the same Markov chain to represent the system. The scaling method in (1) is to ensure that the traffic load for S2 remain the same value, i.e. r2 ¼
l2 l2 ¼ m2 m2
The Markov chain in Figure 1 can be solved numerically [6] to obtain the steady-state probabilities, 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 ; C2 Þ
ð2Þ
The call blocking probability, PB;2 ; for S2 is when no C2 channel is available, i.e. PB;2 ¼
C1 X
pðx1 ; C2 Þ
ð3Þ
x1 ¼0
We can also get from (2) and (3) that the blocking probability of S1 is always lower than that of S2 : The average call blocking probability, PB;ave ; for FCP is given by PB;ave ¼ g1 PB;1 þ g2 PB;2
ð4Þ
2.3. Performance analysis of FCP with switching In the previous channel allocation procedure, we have such situation that some C1 channels are free (because of the departure of the S1 calls) and all the C2 are busy (some C2 channels might be borrowed by S1 calls). If a new S2 call comes into the system, the S2 call is blocked because there is no free C2 channel for S2 call to be used although there are some free C1 channels. So we introduce 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 blocking probability 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 represented by a standard two-dimensional Markov chain as shown in Figure 2. At this time, the states, a and b; represent the numbers of S1 and S2 calls existing in the system, which are different from x and y that we have mentioned in Section B: And the allowable states are given by S ¼ fða; bÞ j 04a4C; b ¼ minfC a; C2 gg: The procedure of assigning or releasing of a channel to a call is same with the previous Markov chain. Except that the overflow and switching are represented by the right part of the Markov chain for all states a5C1 þ 1: For example, the Copyright # 2004 John Wiley & Sons, Ltd.
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Figure 2. Markov chain of the FCP with switching.
state, ðC1 þ 1; 2Þ; means that all the C1 channels are busy and three C2 channels are used with one channel borrowed by S1 call. This standard two-dimensional Markov chain can be solved numerically by a closed product form solution [7] and the steady-state probability for each state is given by Pða; bÞ ¼ P
ra1 rb2 a! b!
ð5Þ
y rx1 r2 ðx;yÞ2S x! y!
So, the blocking probability, P1 ; of S1 is the states that all C1 and C2 channels are busy and is given by X P1 ¼ Pða; bÞ ð6Þ fða;bÞjCC2 4a4C;b¼Cag
and the blocking probability, P2 ; of S2 is the states that all C2 channels are busy and is given by X Pða; bÞ ð7Þ P2 ¼ fða;bÞj04a4C;b¼minfCa;C2 gg
And the average call blocking probability, PB;ave ; for FCP with switching is given by PB;ave ¼ g1 P1 þ g2 P2
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 shortterm 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 Copyright # 2004 John Wiley & Sons, Ltd.
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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 an interference information table (IIT), which contains sufficient information about the status of channels in each interfering cell, to allocate channels to users. DCA-WI tries to manage the channel allocation between cells in a proper way so that each allocation of the channel causes least interference to the neighboring cells. We apply the CP algorithm to this DCA-WI scheme called 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 sufficient information 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. For example, as shown in Tables I and II, there are 28 channels allocated as C1 channels and 182 channels 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 interference cells (I CELL). As shown in Figure 3 for cell 25, if we assume the reuse factor of N1 and N2 are 4 and 7, respectively; there are 12 and 18 interference cells in Tables I and II, respectively. The other 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 is a used channel. For example, in Table II, the cell 25 uses channels 32 and 209 and the cell 39 uses 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 is borrowed by a S1 call in cell 25. A letter L in [I CELL, channel j] box indicates that this channel is used and locked by an I CELL’s interference cell, say cell X; which is not the interference cell of O CELL. This means that channel j is a LOCKED CHANNEL in I CELL and it is not allocated to use in that I CELL. For example, in Table I, channel 2 is locked in cell 12 because one 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 this channel is either a FREE CHANNEL (if there is no U or U 0 in this column) or a LOCKED CHANNEL (if at least one U or U 0 is in this column). For example, in Table II, channel 30 is a FREE 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
25 12 17 18 19 .. . 39
U
2 L L L U
Copyright # 2004 John Wiley & Sons, Ltd.
3
L
4
5
L
L L L L
L
...
27
28
3L L L
U Int. J. Commun. Syst. 2004; 17:575–590
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Table II. IIT of cell 25 for S2 : Channel no. for S2 Cell no. ..25 .. .. ..19 . 38 39
29 U
30
31
32
0
...
33
U
209
210
U U0
2L
L
L U
49 48 42
47 46 45 44 43
40 39
38
33
31 30 23
22
9
14 13
12 11
10
8
20 19
17
15
21
26
18
16
28 27
25 24
29
35 34
32
37 36
41
7 6
5 4
3 2
1 Figure 3. System model for 49 cells with two reuse factors.
19. A LOCKED CHANNEL here means that one or more I CELL(s) of O CELL currently use(s) this channel. 3.2. Channel assignment and reassignment The channel allocation of DCP-WI tries to minimize the effect of the assignment on channel availability in all the interfering cells of O CELL. The idea is to allocate a channel that has been locked by the maximum number of I CELLs. For example, if a new S1 call arrives in cell 25, Copyright # 2004 John Wiley & Sons, Ltd.
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refer to Table I, channel 5 is preferred to be used because assigning channel 5 to this new call will affect 8 I CELLs and these 8 I CELLs cannot use channel 5. If other channel is assigned, more I CELLs will be affected. For example, the assigning of channel 28 will affect 10 I CELLs, which cannot use channel 28. Information about whether a channel j is locked or not in I CELL of O CELL is provided in the O CELL’s IIT. A channel j is locked if there is at least an L in channel j’s column. A channel j with the smallest value of the cost functions, MINfCð jÞ or C 0 ð jÞg; as in (9) and (10), is allocated to the new arrival call in O CELL to use. If that new call cannot get a channel, it is blocked. The cost functions, Cð jÞ or C0 ð jÞ; for channel assignment and reassignment can be used for both S1 and S2 calls. The Cð jÞ for channel assignment is for all free channels in O CELL and is given 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, NðAÞ is 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 shown in Table I. We can see from the function that NðAÞ is pre-defined constant in the system. If we get the maximum value of LðA; jÞ for a channel j; then we can achieve the minimum value of Cð jÞ: To give an extreme case for an example, when channel j in all I CELLs of O CELL are locked, i.e. LðA; jÞ ¼ NðAÞ; then O CELL can use this channel freely without causing any disturbance to its interference cells. Because all these I CELLs are locked and cannot use this channel j: A single channel reassignment is considered here to further improve the system capacity. The C 0 ð 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 in an I CELL in channel j’s column. For example, refer to Table II, channels 31 and 33 are locked channel with a single locked cell in cell 25. When allocating a locked channel j to a new call in O CELL, we may reassign the call using that channel j in I CELL to other channel i in I CELL in order to free channel j in O CELL. The cost function for the single channel reassignment is given by C 0 ð 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 locked cell number of LðB; jÞ and LðB; iÞ are obtained from cell B’s IIT. The purpose of (10) is to minimize the impact on the interference cells of switching the on-going call using channel j to channel i: The costs for all free channels and locked channels with a single locked cell are obtained using Cð jÞ and C0 ð jÞ; respectively. A channel with the lowest cost will be allocated to the new arrival call. 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 be assigned to the new service call. When there is more than one channel with the same smallest Copyright # 2004 John Wiley & Sons, Ltd.
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cost function value, the selection order of the channel is based on the following rules with the first one having highest priority: (1) A channel with a larger number of locked cells has higher priority. For example, in Table I, channel 5 with 4 locked cells, has higher priority than channel 27, with only 1 locked cell. (2) A free channel has higher priority, e.g. in Table I, channel 27 has higher priority than channel 3. (3) If several channels have same number of locked cells, a lower-numbered channel has higher 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 lowernumbered channel has higher priority, e.g. in Table II, channel 31 has higher priority than channel 33.
3.4. Cell updating After assigning or releasing of a channel, the IITs should be updated to the changing status of the channel. When a BS attempts to allocate channel j to its O CELL, the updating procedure follows 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 [O CELL, channel j] in I CELL’s IIT. (3) All the I CELLs inform all of their interference cells, say cell X; which is not the interference 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 its interference cells. The updating procedure for releasing channel is done in the similar way as above except that the ‘inserting’ a letter U or U 0 should be replaced by ‘removing’. The ‘adding’ of a letter L should be replaced by ‘subtracting’. 3.5. Other assignment technique}rearrangement Other assignment techniques such as overflow, switching and rearrangement are applied to DCP-WI in order to enhance the performance. Overflow and switching have been introduced in Section 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 minimize the effect on the interference cells during its service. Many algorithms have been proposed in this area [8, 9]. In DCP-WI scheme, the rearrangement of the channel is also based on the IIT’s information. If a channel j is released in O CELL, an on-going call in O CELL using a channel i with the least number of locked cells will switch to that channel j provided that the number of locked cells in channel j is higher than that in channel i: If more than one channel has the same least number of locked cells, the highest numbered channel will perform the rearrangement. Copyright # 2004 John Wiley & Sons, Ltd.
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Always, the rearrangement will work combined with switching algorithm. The difference between switching and rearrangement is that switching should be performed between two types of channels for S1 calls only while rearrangement is performed between same traffic channels for both services. When a traffic1 channel is released, switching will first be performed. Then, the rearrangement 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. But for 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 technique is used in the multiple cells. That is, in Figure 3, the left most cells are deemed connecting with 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 are assumed to be 4 and 7 for S1 and S2 calls. For both FCA and DCA-WI, a single reuse factor of 7 is used to support both services. Therefore, CFCA is 30 per cell and the total system channel for DCA-WI is 210. The mean call durations, 1=m1 and 1=m2 for S1 and S2 ; are assumed to be 100 and 50 s: The S1 service can be considered as a traditional voice call that requires lower reuse factor and longer call duration time. The S2 service can be considered as a data service. The traffic performance for the connection blocking probability, Pb ; is aimed at 1% for FCP, DCP-WI, DCA-WI and FCA. Different channel combinations, CðC1 ; C2 Þ; for FCP and DCP-WI are simulated to achieve the best performance. Remember that 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 channel pool 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 second traffic load ratio is 1:2, which corresponds to the arrival rate ratio of 0.2:0.8. This can represent the future mobile communication system in which the data traffic will predominate the network. 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 channel combinations, CðC1 ; C2 Þ; 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: As mentioned 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 the best channel combination, Cð35:11Þ; is about 59%. In this case, CFCP ¼ 46: Some simulation results for FCP are also shown in Figures 4 and 5 and they are matched closely with the analytical results. Copyright # 2004 John Wiley & Sons, Ltd.
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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: Copyright # 2004 John Wiley & Sons, Ltd.
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Figure 6. The comparison of DCP-WI over FCA and DCA-WI for r1 :r2 ¼ 1:2 in uniform traffic distribution.
Figure 7. The comparison of DCP-WI over FCA and DCA-WI for r1 :r2 ¼ 8:1 in uniform traffic distribution.
Figures 6 and 7 show the simulation results of DCP-WI over FCA and DCA-WI in uniform traffic distribution scenario. Under low S1 traffic load ratio, e.g. r1 :r2 ¼ 1:2; DCP-WI provides about 38 and 8% improvement over FCA and DCA-WI, respectively. But under high S1 traffic Copyright # 2004 John Wiley & Sons, Ltd.
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Figure 8. The improvement of FCP (with and without switching), DCP-WI over FCA under different traffic load ratios.
load ratio, i.e. r1 :r2 ¼ 8:1; DCP-WI gives about 73 and 36% improvement over FCA and DCA-WI. Figure 8 shows the improvement of FCP, DCP-WI over FCA under different traffic load ratio between S1 and S2 calls. As we can see from the figure, with the increasing of the S1 traffic load ratio, the improvements of FCP and DCP-WI over FCA increase. This is because with the increasing of S1 traffic load, more channels are allocated to support S1 calls for reuse factor of 4 due to more S1 users. So, the overall reuse factor of the channel usage becomes smaller and the system capacity is improved. In the present communication system, the traffic load for 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% improvement over FCP without switching. This shows that the proposed switching technique can provide additional benefit. Compared with FCP scheme, DCP-WI scheme always outperforms FCP. This shows that dynamic channel allocation scheme can further cater for the traffic variations between cells. The performance of DCP-WI algorithm in the non-uniform traffic distribution scenario is studied. The non-uniform distribution model in [12] is used in the simulation. Figures 9 and 10 show the simulation results of DCP-WI over DCA-WI and FCA algorithm under the traffic load ratio of 1:2 and 8:1, respectively. From the figures we can find that the conclusion of DCPWI algorithm over DCA-WI algorithm is same as we get in the fixed cellular system model. That Copyright # 2004 John Wiley & Sons, Ltd.
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Figure 9. The comparison of DCP-WI over FCA and DCA-WI for r1 :r2 ¼ 1:2 in non-uniform traffic distribution.
Figure 10. The comparison of DCP-WI over FCA and DCA-WI for r1 :r2 ¼ 8:1 in non-uniform traffic distribution.
is with the increasing S1 traffic load ratio, the improvement of DCP-WI over DCA-WI is also increasing. The improvements with the best channel combination of DCP-WI over DCA-WI under these two traffic scenarios are 9 and 33%. But as compared with FCA algorithm, DCPCopyright # 2004 John Wiley & Sons, Ltd.
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WI can always provide better improvement. The improvement is 98 and 143% in these two traffic scenarios. In conclusion, DCP-WI is able to cater for the non-uniform distribution environment.
5. CONCLUSION AND FUTURE WORK This paper proposes an idea of channel partitioning (CP) employing different reuse factors to support multiple services requiring different SIRs. The analysis of the proposed idea of CP is first introduced with fixed channel allocation scheme. Then, the applying of this CP with a previously proposed dynamic channel allocation scheme is followed. Two types of services are considered in this paper. The results under both uniform and non-uniform traffic distribution scenarios show that our proposed algorithms can improve the system capacity depending on the traffic load ratio between services. With increasing traffic load for service requiring small reuse factor, the improvement of the proposed schemes over other channel allocation schemes using a single reuse factor increases. For equal arrival rate for both services, FCP and DCP-WI provide about 33 and 60% capacity improvement respectively over a conventional FCA system using a single reuse factor to support two types of services. The disadvantage of the current schemes is that the best channel combination (which can provide the best system performance) depends on traffic load ratio. In other words, different traffic load ratio requires different best channel combination. But it is not adaptive enough because the network traffic load ratio may change from time to time. So our future work will focus on another channel allocation scheme that can flexibly allocate the channels to meet the network variation such that no pre-allocation of channels to each service is required.
REFERENCES 1. Holma H, Toshala A. WCDMA for UMTS (2nd edn). Wiley: New York, 2002. 2. Choi J, Silvester JA. A fair-optimal channel borrowing scheme in multiservice cellular networks with reuse partitioning. Proceedings of IEEE ICUPC ’98, vol. 1, 1998; 261–265. 3. Zhao D, Shen X, Mark JW. Performance analysis for cellular systems supporting heterogeneous services. Proceedings of IEEE ICC, vol. 5, May 2002; 3351–3355. 4. Lee S-H, Lim J-S. Performance analysis of channel allocation schemes for supporting multimedia traffic in hierarchical cellular systems. IEICE Transactions on Communications 2003; E86-B:1274–1285. 5. Peter HJ Chong, Cyril Leung. A network-based dynamic channel assignment scheme for TDMA cellular systems. International Journal of Wireless Information Networks 2001; 8(3):155–165. 6. Kleinrock L. Queueing Systems, vol. 1: theory. Wiley: New York, 1975. 7. Bertsekas D, Gallager R. Data Networks (2nd edn). Prentice-Hall: New Jersey, 1991; 180–184. 8. Chang K, Kim J, Yim C, Kim S. An efficient borrowing channel assignment scheme for cellular mobile systems. IEEE Transactions on Vehicular Technology 1998; 57(2):602–608. 9. Zhang M, Yum T. Comparisons of channel assignment strategies in cellular mobile telephone systems. IEEE Transactions on Vehicular Technology 1989; 38(4):211–215. 10. Rao YS, Roy MN. Mixed voice and data capacity estimation for 3G wireless network. Commsphere 2000, Session 6.1, February 2000. 11. UMTS TR 101 112 Ver3.1. Selection of radio transmission technology. November 1997. 12. Yeung K, Yum T. Compact pattern based dynamic channel assignment for cellular mobile systems. IEEE Transactions on Vehicular Technology 1994; 43(4):892–896.
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M. YANG AND P. H. J. CHONG AUTHORS’ BIOGRAPHIES
Ming Yang was born in Shenyang, China, on October 18, 1978. He received the BS degree in Information engineering (English intensive) from Dalian University of Technology, China, in 2002. Since October 2002, he has been pursuing his PhD degree at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His research interests include handoff, channel allocation, and radio resource management for present and future mobile communication systems.
Peter H. J. Chong was born in Hong Kong, China, on June 4, 1970. He received the BEng (with distinction) in electrical engineering from the Technical University of Nova Scotia (currently Dalhousie University), Halifax, NS, Canada, in 1993, and the MASc. and PhD degrees in electrical engineering from the University of British Columbia, Vancouver, BC, Canada, in 1996 and 2000, respectively. Between July 2000 and January 2001, he worked with Advanced Networks Division at Agilent Technologies Canada Inc., Vancouver, BC, Canada. Between February 2001 and May 2002, he was a Research Engineer in the Radio Communications Laboratory at Nokia Research Center, Helsinki, Finland, and was involved in research on WCDMA and standardization. Since May 2002, he has been with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 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.
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