Video Services in a Round-Robin Carrier-Hopping Multi ... - CiteSeerX

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 6, NO. 3, MARCH 2007

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Video Services in a Round-Robin Carrier-Hopping Multi-Rate Multi-Carrier DS-CDMA System David Tung Chong Wong, Senior Member, IEEE, Jon W. Mark, Life Fellow, IEEE, and Kee Chaing Chua, Member, IEEE

Abstract— The type of services and the manner with which multiple access is performed have a tremendous impact on the system capacity. The capacity region for video services in the uplink of a round-robin carrier-hopping multi-rate Multi-Carrier (MC) DS-CDMA cellular system is derived by formulating and analyzing the outage probabilities in terms of bit error rate specifications. The subcarriers of the MC-DS-CDMA system are dynamically allocated to evenly distribute their usage. Three management schemes are used to perform subcarrier allocation: complete sharing (CS), dynamic complete partitioning (DCP) and dynamic complete group partitioning (DCGP). The analytical framework is formulated for the general case in which different traffic classes have different spreading gains in each of the subcarriers. Numerical results show that the capacity of DCGP is larger than that of CS or DCP. Index Terms— multi-rate Multi-Carrier DS-CDMA, roundrobin carrier-hopping, uplink capacity, video services, complete sharing, dynamic complete partitioning, dynamic complete group partitioning, outage probability, capacity region, quality of service.

I. I NTRODUCTION G cellular mobile networks are expected to support integrated multimedia services with different quality of service (QoS) requirements for different service classes, and with a data rate of at least 10 times that for 3G. From the service provider’s point of view, the most critical aspect of the increased service offerings is to increase revenue. Since a large network capacity region leads to increased revenue, it is thus particularly relevant to assess the capacity region of wireless cellular CDMA networks that support multimedia services in general and video services in particular, since the latter places a heavier demand on system bandwidth than other services. There have been many papers appeared in the literature which address the capacity of wireless cellular CDMA networks, e.g., [1-3]. However, most of these papers consider only one or two traffic classes. For 3G/4G cellular systems, many types of connections are anticipated, not just voice

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Manuscript received April 7, 2004; revised April 21, 2005, April 10, 2006, August 24, 2006, and September 15, 2006; accepted September 15, 2006. The editor coordinating the review of this paper and approving it for publication was M. Zorzi. The work of the second author has been supported by the Natural Sciences and Engineering Research Council of Canada under Grant no. RGPIN7779. D. T. C. Wong is with the Institute for Infocomm Research, A*STAR, Singapore (email: [email protected]). J. W. Mark is with the Centre for Wireless Communication, University of Waterloo, Canada (email: [email protected]). K. C. Chua is with the Department of Electrical and Computer Engineering, National University of Singapore, Singapore (email: [email protected]). Digital Object Identifier 10.1109/TWC.2007.05284.

and data traffic. The connections could be voice, video, data, multimedia, web browsing, email, etc., i.e., we have multiclass traffic. In [4], we have generalized the analysis in [3] for two traffic classes to K traffic classes. Also, in most performance analyses of the system capacity [1-4], the traffic source is often assumed to be an on/off process which enables simple closed-form solutions. However, this assumption is valid only for voice or data traffic but not for video traffic with slow and fast motion scene changes, which is expected to be a major component of the traffic in 4G systems. The video services envisioned are of many types, such as video phone, video conferencing, entertainment video, etc. Such a video source can be represented as in Sen’s video model [5-7] where each source is modeled by a two-dimensional Markov chain to represent a combination of low and high bit rates. The low bit rates account for scenes with slow motion while the high bit rates account for scenes with fast motion. A special case of Sen’s video model is Maglaris’ video model [8] which considers only scenes with low bit rates and hence can be modeled by a one-dimensional Markov chain. We have analyzed the system capacity of a wideband CDMA system with Maglaris’ video model in [9], which considers variable bit rate (VBR) traffic, but does not account for scene changes when applied to video services. In [10], we have analyzed the system capacity for video traffic with scene changes in a multi-rate direct-sequence (DS) CDMA system. Recently, Multi-Carrier (MC) CDMA systems have been receiving a lot of attention as they promise high data rates required by 4G mobile cellular systems and they are effective in mitigating multipath fading and rejecting narrowband interference [11-16]. In this paper, we focus on a non-overlapping frequency bands MC-DS-CDMA scenario. It is noted that an MC-DS-CDMA system with disjoint bandwidths has been considered in [11-13], where each disjoint band (subcarrier) constitute a single DS-CDMA system [11, Figs. 11.2 and 11.3]. In [12], a random carrier-hopping policy has been considered where the subcarriers used for transmission are randomly selected within the allocated/usable set of subcarriers according to some subcarrier allocation schemes. The random selection of subcarriers by a user is assumed to exclude selection of the same subcarrier for each level of transmission, i.e., only one level of transmission is allowed in each subcarrier by a user. In [13], an MC-DS-CDMA scheme has been proposed to yield both frequency diversity improvement and narrowband interference suppression. In [14] three types of multi-carrier CDMA systems, viz.,

c 2007 IEEE 1536-1276/07$25.00

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MC-CDMA, MC-DS-CDMA, and multi-tone CDMA, have been considered. The MC-DS-CDMA system in [14, Fig. 4] considers an overlapping bandwidths scenario and is not the conceptual non-overlapping bandwidth scenario considered in this paper. More details of these schemes can be found in [1519]. A random carrier-hopping DS-CDMA system has been considered in [20], which allows for the selection of the same subcarrier for each level of transmission, i.e., more than one level of transmissions are allowed in each subcarrier by a user. An MC-DS-CDMA scheme which transmits the same data using several subcarriers has been proposed in [21]. The main concern of this work is the support of video services with scene changes in an MC-DS-CDMA system. Of particular interest is the capacity region available for video services. The capacity in the uplink is defined as the largest number of users that can be supported in each traffic class during any one use of the uplink. For multi-rate traffic such as video, during any transmission epoch a single source may transmit over a number of subcarriers, each using the same spreading code. To avoid over-utilizing some of the subcarriers and under-utilizing others in successive transmission epochs, we propose to hop the transmissions by the same source in successive transmission epochs over the entire set of subcarriers using a round-robin transmission discipline to evenly distribute the energy. The aim is to allocate subcarriers to the multi-class traffic in such a way as to evenly distribute the energy for all traffic classes. This has the effect of minimizing the outage in the subcarriers. We coin this transmission plan as round-robin carrier-hopping multi-rate MC-DS-CDMA. To allow a given source to transmit across different subcarriers is a resource (subcarrier) allocation problem. Conventional resource allocation uses either complete sharing (CS) or complete partitioning (CP). CS or CP is appropriate when the total resource (capacity) is hard. In CDMA-based systems, the capacity is soft and is dependent on both intra- and intercell interference. To minimize the effect of interference, we introduce two methods to dynamically allocate subcarriers: Dynamic Complete Partitioning (DCP) and Dynamic Complete Group Partitioning (DCGP). The difference between DCP and DCGP is that, in the latter case, for the purpose of subcarrier allocation, the users are formed in groups. The motivation for using DCP and DCGP is to partition the subcarriers such that intra-cell and inter-cell interferences from other classes are eliminated for both schemes and some of the interference from its own class is also eliminated for DCGP. The major contributions of this work are (i) the distribution of the energy of a video source amongst the subcarriers in a round-robin carrier-hopping MC-DS-CDMA system using a CS/DCP/DCGP subcarrier allocation strategy, and (ii) the analytical formulation and derivation of the capacity regions in support of video services that satisfy the bit error rate requirements of all traffic classes 99% of the time in the uplink. It is noted that the capacity region is directly affected by the quality of service (QoS) specification. Here, 99% is considered acceptable, as opposed to the more stringent requirement of 100% of the time. The rest of the paper is organized as follows. Section II states the problem addressed in this paper. Section III describes the details of the proposed round-robin carrier-

hopping multi-rate MC-DS-CDMA multiple access plan. Section IV discusses the video source model to facilitate analytical evaluation. An analytical model for video services with scene changes in the round-robin carrier-hopping multi-rate MC-DSCDMA system is presented in Section V. Numerical results for two traffic classes are presented in Section VI. Finally, concluding remarks are given in Section VII. II. P ROBLEM S TATEMENT We consider the transmission of video traffic in the uplink of a wireless cellular round-robin carrier-hopping multi-rate MC-DS-CDMA network with variable spreading gain in each subcarrier. Of particular interest is the uplink capacity in terms of the number of users, ni , that can be supported for the ith class. The capacity of a K-class system in the uplink is defined by (n1 ,n2 ,...,nK ). The capacity region for K classes is derived by considering the outage probability in each subcarrier in terms of the signal-to-interference ratio (SIR) specification. III. ROUND -ROBIN C ARRIER -H OPPING M ULTI -R ATE MC-DS-CDMA In multi-carrier CDMA systems, e.g., CDMA 2000, the bandwidth of the transmission channel is partitioned into several subbands, each of which is associated with a subcarrier. The bandwidth of the signal transmitted over any one subband is only a fraction of that would be transmitted over a wideband CDMA system, e.g., WCDMA in 3G. The availability of multiple subcarriers facilitates the opportunity for a user’s transmission to hop over several subbands to combat multiuser interference. In multi-carrier CDMA systems, the number of subcarriers may not be very large, e.g., 3 in CDMA 2000. The transmitted signal bandwidth may still be large compared to the coherence bandwidth of the transmission subchannel, resulting in frequency selective fading. Orthogonal frequency division multiplexing (OFDM), also has multiple subcarriers, is used to combat frequency selective fading, e.g., in 3G systems. In principle, multi-carrier, as discussed in this paper, and OFDM signaling can be deployed in tandem to combat channel impairments and interference. In recent years, MC-DS-CDMA systems have received great attention because of their potential for high-speed transmission which is expected for 4G systems. For the MC-DS-CDMA system under consideration, each subcarrier has a spreadspectrum bandwidth of W/Nc , where W is the spread-spectrum bandwidth and Nc is the total number of subcarriers. The cth subcarrier has center frequency fc , c = 1,2,...,Nc. The same spreading code can be used by a user in each of the subcarriers. A. Representation of Variable Bit Rate Video Source Fig. 1 shows a variable bit rate video source with discrete bit rate levels. Each level has a bit rate of Ri,l , where i = 1,2,...,K, K is the number of traffic classes in the uplink and the subscript l denotes low bit rate. The overall bit rate level is a function of the sum of low bit rate and high bit rate levels. The highest level for low bit rate fluctuation is Mi and the level for high bit rate fluctuation is either zero or Xi . It is proposed to convert the high bit rate levels into low bit rate levels so that the transmission rate in each

WONG et al.: VIDEO SERVICES IN A ROUND-ROBIN CARRIER-HOPPING MULTI-RATE MULTI-CARRIER DS-CDMA SYSTEM

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fH+1

Bit rate level fL+3

M i

X i

Variable bit rate video stream

Spliter for parallel video substream

Roundrobin subcarrier allocator

fL+2

Transmitted signals

fL+1

X i M i

fL

2 1

Reference video substream Subsequent video substream

t1 t 2 Fig. 1.

t3

t 4 t5

t6 t7

t8 t9

t10

time

A single carrier DS-CDMA transm itter with centre frequency,fc, bandwidth of W/Nc, and a spreading gain ofG i for a class i user, where c=L,L+1,…,H, L is the lowest subcarrier allocated,H is the highest subcarrier allocated,W is the total bandwidth of all subcarriers andNc is the total number of subcarriers

fc

(a)

Bit rate of a video source. fH

subcarrier is based on low bit rate levels only. The reason for this conversion is because transmission of low bit rate levels allows larger symbol times and smaller delay spreads in each of the subcarriers compared to high bit rate transmissions. This is in the same line of thought for MC-DS-CDMA. In Fig. 1, the low bit rate fluctuation is represented by the thin solid line, the high bit rate fluctuation is represented by the dash line, and the total bit rate is represented by the thick solid line. Thus it has the highest bit rate of (Mi +Xi )Ri,l . Each level of bit rate is transmitted through one subcarrier. A variable bit rate video stream is thus transmitted through a number of subcarriers, each using the same spreading code. In each subcarrier, there can be a different class of users, each transmitting at different bit rates, Ri,l . Every user in the same class transmits at the same bit rate in each of the subcarriers that they are transmitting. For ease of illustration, the time durations at each level for a source are shown equal in Fig. 1. B. MC-DS-CDMA System Model For subcarrier allocation, all the subcarriers can be (a) completely shared by all classes, (b) dynamically completely partitioned, or (c) dynamically completely group partitioned. To evenly spread the usage of the subcarriers and outage probabilities in the subcarriers, and to increase the system capacity, it is proposed to use the round-robin carrier-hopping multi-rate MC-DS-CDMA as the multiple access mechanism in each case. Note that a round-robin carrier-hopping scheme is easier to implement than a random carrier-hopping scheme. The MC-DS-CDMA system model with variable bit rate video stream at the transmitter and receiver sides is shown in Fig. 2. Each of the subcarriers behaves as a single carrier DS-CDMA system. At the transmitter (Fig. 2a), the variable bit rate video stream is split into video substreams each corresponding to a low bit rate level. A round-robin subcarrier allocator is then used to allocate the subcarriers that the video substreams are to be transmitted in. Each substream is transmitted through a single carrier DS-CDMA transmitter with non-overlapping bandwidth from other single DSCDMA transmitters transmitting other video substreams. The subcarriers are selected with the reference video substream moved in a round-robin manner over the allocated subcarriers. The round robin scheme assigns the next subcarrier to the

fL+3 Received signals

fL+2 fL+1

Realignment of parallel video substream

Combiner to obtain received video stream

Received variable bit rate video stream

fL

fc

A single carrier DS-CDMA receiver with centre frequency, fc, bandwidth of W/Nc, and a spreading gain ofG i for a class i user, where c=L,L+1,…,H, L is the lowest subcarrier,H is the highest subcarrier, W is the total bandwidth of all subcarriers andNc is the total number of subcarriers

(b)

Fig. 2. MC-DS-CDMA system model with variable bit rate video stream at (a) the transmitter, and (b) the receiver.

reference video stream in a known cyclic order after every fixed frame time within the subcarriers that it can transmit in. The subsequent video substreams are assigned subcarriers with reference to the reference video substream. Thus, the goal of evenly spreading the usage of the subcarriers is achieved and the outage probabilities in the subcarriers are lowered and the number of users that can be supported is increased. Let L and H represent, respectively, the lowest and highest subcarrier numbers. The subcarriers allocated by the roundrobin subcarrier allocator depend on the subcarrier allocation scheme used. The allocated subcarriers range from the lowest subcarrier allocated, L, to the highest subcarrier allocated, H. The three schemes considered in this paper are CS, DCP and DCGP. For CS, each user can use all of the subcarriers. Thus L = 1 and H = Nc , where Nc is the total number of subcarriers. For DCP, the subcarriers allocated are dynamically completely partitioned such that users of classes do not the share different i−1 i same subcarriers. Thus L= j=1 Ncj + 1 and H= j=1 Ncj , where Nci is the number of subcarriers K allocated to a class i user, Nci > Zi , Zi =Mi +Xi , and i=1 Nci =Nc . For DCGP, the subcarriers allocated are dynamically and completely group partitioned such that users of different classes do not share the same subcarriers and users within the same class are further divided into groups i−1that do not share the same subcarriers. In this case, L= j=1 Ncj + (g − 1)Zi + 1 and i−1 H= j=1 Ncj + gZi , where g=1,...,Ngi denotes the gth group that the class i user belongs and Ngi = Nci /Zi is the number of groups in class i. Fig. 3 shows the round-robin subcarriers

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Fig. 3. Round-robin subcarriers allocation for the CS, DCP and DCGP schemes.

allocation for the CS, DCP and DCGP schemes with 2 classes. For the DCGP scheme, each of the two classes has 2 groups. Note that the number of subcarriers in both classes is Zi =3 and Nc =12, Nc1 =Nc2 =6. The complete partitioning and complete group partitioning of the subcarriers to different classes are dynamically adjusted to maximize the number of users that can be supported by using the DCP and DCGP admission region curves in Section VI. The DCP and DCGP admission regions can be stored in lookup tables and be referenced to execute the dynamic complete partitioning or dynamic complete group partitioning allocation of subcarriers to each class when DCP can support more users than CS or when DCGP can support more users than either CS or DCP. For DCP, as shown in Fig. 3, the number of subcarriers allocated to each class is six. For example, during the dynamic execution of DCP, the boundary between the two classes could vary from 3 subcarriers for class 1 users and 9 subcarriers for class 2 users to 9 subcarriers for class 1 users and 3 subcarriers for class 2 users. That is, Nc1 varies from 3 to 9 while Nc2 (=Nc − Nc1 ) varies from 9 to 3. During the dynamic execution of DCGP, the boundary between the two classes could vary from 3, 6 and 9 subcarriers for class 1 users, and 9, 6 and 3 subcarriers for class 2 users, respectively. That is, Nc1 varies from 3, 6 and 9 while Nc2 varies from 9, 6 and 3. At these values, the number of groups in class 1, Ng1 = 1, 2 and 3, while the number of groups in class 2, Ng2 = 3, 2 and 1, respectively. The allocation of a subcarrier group to a new class i user can be cyclic or based on selecting the group with the least number of users to balance out the traffic load in that class. In a practical scenario, additional coordination between base stations is needed for the DCP and DCGP schemes. At the receiver, as shown in Fig. 2b, each of the received video substreams is recovered by a single carrier DS-CDMA receiver with non-overlapping bandwidths from other single DS-CDMA receivers recovering other video substreams. The video substreams are then realigned and combined to obtain the received variable bit rate video stream. IV. V IDEO S OURCE M ODEL The video traffic model used in this paper is a classical model developed in [5-7], which is analytically tractable. A class i VBR video source can be modeled by a 2-dimensional continuous-time Markov chain with finite states as shown in Fig. 4, where the state is represented by the 2-tuple (x,m), x = 0,1; m = 0,1,...,Mi. Each state (x,m) represents the combined

Fig. 4. 2-Dimensional Continuous-Time Markov chain for a single VBR video source.

discrete level of low and high bit rates that are generated by a single source. The combined data rate of each class i source is (mRi,l +xRi,h )=(m+X)Ri,l , where X∈{0, Xi }, Ri,l is the low bit rate for a class i user using one low bit rate spreading code and Ri,h is the high bit rate for a class i user. The high bit rate level is converted to its equivalent low bit rate level so that only equivalent low bit rate spreading codes are used in the subcarriers. We assume that each level of low bit rate uses one spreading code in one subcarrier for a class i user. This means that each level has a data rate of Ri,l corresponding to one class i spreading code. Every user uses the same spreading code in its subcarriers. Each low bit rate level is modeled by a two-state mini-source with an increase rate of αi and a decrease rate of βi . Thus the 2-dimensional continuous-time Markov chain for a single video source at state (x,m) has an increase rate of (Mi − m)αi and a decrease rate of mβi for low bit rate fluctuations, where Mi is the highest level in the low bit rate states. This is also the maximum number of active spreading codes used by a class i user for low bit rate fluctuations. Each high bit rate fluctuation is modeled by a two-state Markov chain with an increase rate of λi and a decrease rate of μi . There are only two states in the high bit rate fluctuation x∈{0,1}; state 0 (x = 0) means that there is no high bit rate fluctuations but only low bit rate fluctuations, while state 1 (x = 1) means that there are both low and high bit rate fluctuations. If the high bit rate fluctuation has only one state (state 0), then it reduces to Maglaris’ model. Furthermore, if Mi = 1, the source is an on/off source. The steady-state probability of being in state x, denoted by Qx , is given by 1 − qi , x = 0 Qx = (1) qi , x=1 where qi = λi /(λi + μi ). The steady-state probability of being in state m, denoted by Pm , is given by [6] Mi Pm = pi m (1 − pi )Mi −m , m = 0, 1, 2, ..., Mi , (2) m


where pi = αi /(αi + βi ). Let y = m + X, where m ∈ {0, 1, ..., Mi }, X ∈ {0, Xi } and y ∈ {0, 1, ..., Mi + Xi }. Therefore, the probability mass function of y, denoted by Py , is given by

Py =

Mi 1

Qx Pm , if (y = M +X), y = 0, 1, ..., Mi +Xi ,

x=0 m=0

x = 0 ⇒ X = 0, x = 1 ⇒ X = Xi . (3)

V. A NALYTICAL M ODEL

In this work, the underlying multiple access mechanism is round-robin carrier-hopping MC-DS-CDMA. The propagation channel is assumed to exhibit path loss with a path exponent equal to 4, and shadowing with a lognormal distribution. The system capacity differs, depending on whether CS, DCP or DCGP is used to perform subcarrier allocation. The analytical development is as follows. Firstly, the spreading code activity factors in a subcarrier for the different allocation schemes are determined. Secondly, the signal-to-interference ratios for these allocation schemes are formulated. Finally, the outage probabilities in a subcarrier for each of these allocation schemes are formulated using Gaussian approximation. As each of these subcarriers is statistically identical, the outage probabilities for these schemes are the same as those in a subcarrier. The analytical framework developed in this section takes into consideration the following. Assumptions: • • • • •

Users are uniformly distributed in each cell. There is an equal number of users from the same class in every cell. There is perfect power control so that the received signals at the base station are at the same power level. Different traffic classes can have different spreading gain. The spreading gain is the same within the same class.

The first three assumptions are used in [1,3], while the last two are used in [3]. Except for the differences in (i) the total interference under the different subcarrier allocation schemes and (ii) the number of subcarriers associated with the particular subcarrier allocation scheme used, the following remarks hold for all three subcarrier allocation schemes analyzed in the sequel. Remark 1: With the round-robin carrier-hopping subcarrier allocation schemes, if Mi = 1 and x = 0 only, the source is an on/off source and the probability that subcarrier c is used for transmission is simply equal to the source activity factor, pi , divided by the number of subcarriers used by that particular subcarrier allocation scheme, e.g., Nc for CS, Nci for DCP and Zi = Mi + Xi for DCGP. The probability that subcarrier c is used for transmission with different subcarrier allocation schemes given that a class i source is in state y, denoted by

997

Pc|y , is given by ⎧ y/Nc , y = 0, 1, ..., Zi , c = 1, 2, ..., Nc, Zi < Nc (CS) ⎪ ⎪ ⎪ ⎪ ⎪ y/Nci , y = 0, 1, ..., Zi , ⎪ ⎪ ⎪ ⎨ c = i−1 N + 1, ..., i N , Z ≤ N (DCP) i ci j=1 cj j=1 cj Pc|y = ⎪ y/Zi , y = 0, 1, ..., Zi , ⎪ ⎪ i−1 i ⎪ ⎪ ⎪ c = j=1 Ncj + (g − 1)Zi + 1, ..., j=1 Ncj + gZi , ⎪ ⎪ ⎩ Zi ≤ Nci (DCGP) (4) Unconditioning the dependency on state y, the probability that subcarrier c is used for transmission of a class i source with different subcarrier allocation schemes, denoted by Pc , is given by ⎧ y¯ ⎪ Z i ⎨ Nc , Zi < Nc (CS) Pc = Pc|y Py = Ny¯ci , Zi ≤ Nci (DCP) (5) ⎪ ⎩ y¯ y=0 Zi ≤ Nci (DCGP) Zi , Zi where y¯ = y=0 yPy . Remark 2: On the basis that the subcarriers are orthogonal to each other, we model each subcarrier as though it has on/off multi-class traffic with their multi-rate MC-DS-CDMA sources’ subcarrier activity factors being treated like the on/off sources’ activity factors. Let γi denote the Eb /I0 for a class i user in each subcarrier in the uplink, where Eb is the signal energy and I0 is the interference power spectral density. In general, γi can be expressed as γi =

Gi total interference terms pertaining to the subcarrier allocation scheme used

(6)

where Gi is the class i processing gain in each subcarrier. For the different subcarrier allocation schemes, γi is given by ⎧ Gi ⎪ nk Sk ni −1 Ik η , K K ⎪ ψ ⎪ ij + j=1 k=1,k = i k=1 Si + Si j=1 ψkj Si + ⎪ ⎪ ⎪ ⎨ i = 1, 2, ..., K(CS) γi = (7) Gi , i = 1, 2, ..., K(DCP) ni −1 I ⎪ ⎪ ψij + Si + Sη ⎪ j=1 i i ⎪ ⎪ ⎪ ⎩ ngi −1 Gi Ii η , i = 1, 2, ..., K(DCGP)

j=1

ψij + S + S i

i

where ψij ∈ {0, 1} is a Bernoulli random variable indicating the activity factor of the spreading code used by the jth user of class i in a subcarrier. The probability that an active spreading code in a subcarrier is used by source i, denoted by Pr[ψij =1] = ti , is given by P r[ψij = 1] = ti = Pc , i = 1, 2, ..., K.

(8)

The terms in the denominator of equation (7) have the following significance. For CS, the first term is due to the intra-cell interference in subcarrier c from other users in class i, the second term is due to the intra-cell interference in subcarrier c from users belonging to other classes, the third term is due to the inter-cell interference in subcarrier c from all classes and the last term is due to background noise in subcarrier c. For DCP, the first term is due to the intra-cell interference in subcarrier c from other users in class i, the second term is due to the inter-cell interference in subcarrier c from users belonging to the same class, and the last term is

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due to background noise in subcarrier c. Note that by using the proposed DCP scheme, the intra- and inter-cell interference in subcarrier c from other classes are eliminated. For DCGP, the first term is the intra-cell interference in subcarrier c from other users in class i belonging to the same group, the second term is the inter-cell interference in subcarrier c from users in the same class, belonging to the same group, and the last term is due to the background noise in subcarrier c. ngi is the number of class i users in the group. The number of class i users, denoted by ni , is given by ni = Ngi ngi . By the grouping concept, the proposed DCGP scheme eliminates the intra- and inter-cell interference in subcarrier c from other classes and intra- and inter-cell interference in subcarrier c from some of its own class in the other groups. Equation (7) for CS can be rearranged as K

ti (ni − 1)Si +

SiGi =− I k − η, γi K

tk n k S k −

k=1,k=i

k=1

i = 1, 2, ..., K. (9) For i = k, the power ratio can be expressed as Sk = Si

Gi γi Gk γk

+ ti + tk

, i, k ∈ {1, 2, ..., K}, i = k.

(10)

From [3], the inter-cell interference-to-signal ratio in subcarrier c for the jth user in class i is given by Iij = Si

rm rd

4

10(d−m )/10 ,

(11)

where rd is the distance between the inter-cell mobile that is causing interference and the intra-cell base station, rm is the distance between the inter-cell mobile and its own base station, and d and m are Gaussian random variables with zero mean and standard deviation σ. Since d and m are independent, (d - m ) is a Gaussian random variable with zero mean and variance 2σ 2 . The mean and variance of Ii /Si are upper bounded by [3]

rm Ii (12) f E ≤ ti ρ i dA = μii , Si rd and

rm rd

rm rd

8

2

e( 5 ) (15) √ 2σ 2 ln10 40log(rd /rm ) √ , × 1−Q − 5 2σ 2 =

σln10

√ ∞ 2 and Q(y) = y e−x /2 dx/ 2π . The random variable, Ik /Si , can be expressed as Ik I1 Sk = Si S1 Si

Ik Sk

I1 S1

, i, k = 1, 2, ..., K.

(16)

Thus, the mean and variance of Ik /Si satisfy the following inequalities: Ik S k tk ρ k (17) E ≤ μ11 , Si S i t1 ρ 1 and

2 Ik Sk 2 V ar σkk . ≤ Si Si

(18)

Remark 3: The capacity region in each case is derived by analyzing and evaluating the outage probability, defined as P r[BERi ≥ BERi∗ ] where BERi∗ is the bit error rate requirement in a subcarrier for class i users. The outage probability is a function of the active spreading codes and the probabilities of the active spreading codes used in a subcarrier, and the number of active spreading codes used in the subcarrier for all classes. In what follows, we obtain expressions for outage probabilities by invoking the central limit approximation. It has been shown that Gaussian approximation is a good approximation for modeling the multiple access interference for large number of users and moderate to large processing gain [22]. References [1,3,15,23,24] also assumed the Gaussian approximation. Let SIRi∗ denote the SIR requirement in a subcarrier for class i users. The system capacity is defined as the maximum (n1 ,...,ni ,...,nK ) that can be supported such that the achieved SIR in a subcarrier is greater than or equal to the required SIRi∗ in the subcarrier T% of the time for all classes. P r[BERi ≥ BERi∗ ] is equivalent to P r[SIRi ≤ SIRi∗ ]. The outage probability in a subcarrier using different subcarrier allocation schemes can thus be defined as

Ii rm rm 2 , ti g ≤ ρi − t2i f 2 dA = σii Si rd rd (13) 2 is the where μii is the upper bound on the mean of Ii /Si , σii upper bound on the variance of Ii /Si , and ρi is the density √ of class i users per unit area and√is given by ρi = 2ni / 3 for CS and DCP, while ρi = 2ngi / 3 for DCGP, V ar

f

g

rm rd

rm rd

4

2

e( 10 ) √ 40log(rd /rm ) 2σ 2 ln10 √ , × 1−Q − 10 2σ 2 (14) =

σln10

P r[BERi ≥ BERi∗ ] = P r[SIRi ≤ SIRi∗ ] ⎧ ni −1 K nk ⎪ Sk ⎪ Pr ⎪ j=1 ψkj Si j=1 ψij + k=1,k=i ⎪ ⎪ ⎪ ⎪ ⎪ K Ik ⎪ ⎪ + ≥ δ ⎨ i , (CS), k=1 Si = ni −1 ⎪ Ii ⎪ ψ + ≥ δ P r ⎪ ij i , (DCP), j=1 ⎪ Si ⎪ ⎪ ⎪ ⎪ ngi −1 ⎪ Ii ⎪ ψ + ≥ δ ⎩P r ij i , (DCGP), j=1 Si

(19)

η i where δi = G γi − Si , i = 1, 2, ..., K. Note that ni is related to ngi by ni = Ngi ngi .


TABLE I

By Remark 3, equation (19) can be expressed as

PARAMETER VALUES U SED .

μi

=

and

σi

=

⎧ K ⎪ ti ρi Sk ⎪ li + k=1,k=i Si lk + t1 ρ1 μ11 ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ K ⎪ Sk tk ρk ⎪ ⎨ + k=1,k=i Si t1 ρ1 μ11 , (CS), ⎪ ti ρi ⎪ ⎪li + t1 ρ1 μ11 , (DCP), ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ti ρi ⎪ ⎩li + t1 ρ1 μ11 , (DCGP), ⎧ 2 ⎪ ⎪ K ⎪ 2 2 , (CS), ⎪ σii + k=1,k=i Sk σkk ⎨ Si 2 , (DCP), ⎪ σii ⎪ ⎪ ⎪ ⎩ σ 2 , (DCGP). ii

(21)

Symbol Nc M1 M2 α1 β1 α2 β2 q1 q2

Value 20 or 40 or 60 2 2 0.7 0.3 0.9 0.1 0.375 0.375

Symbol T BER∗1 BER∗2 σ γ1 γ2 S1 /η S2 /η μ11 (CS)

R1,l

60 kbps

2 (CS) σ11

R2,l

80 kbps

2 (CS) σ22

R1,h R2,h W Gi

120 kbps 160 kbps 50 MHz (w/Nc )/Ri,l

μ11 (DCGP) 2 (DCGP) σ11 2 (DCGP) σ22

1.E-01

Anal-Class 1 outage prob. for DCP w/o ici

N g1 =2

Anal-Class 1 outage prob. for CS w/o ici

N g2 =3

1.E-02

Value 99 10−3 10−3 8 dB 7 dB 7 dB -2 dB (S1 /η)×(S2 /S1 ) 0.070949n1 or 0.035474n1 or 0.023649n1 0.020991n1 or or 0.010619n1 0.0071071n1 0.024787n2 or 0.012568n2 or 0.0084173n2 0.35474ng1 0.095033ng1 0.10998ng2

Anal-Class 1 outage prob. for DCGP w/o ici

N c =20 N c1 =8 Pr[BER1 >BER*1 ]

P r[BERi ≥ BERi∗ ] ⎧n1 ni −1 nK ⎪ l1 =0 ... lK =0 li =0 ... ⎪ ⎪ ⎪ K Ik ⎪ Sk ⎪ ⎪ Pr ≥ δi − l i − K ⎪ k=1 k=1,k=i lk Si S i ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ψ1j = l1 , ψ2j = l2 , ..., ψKj = lK ⎪ ⎪ ⎪ ⎪ ⎪ ⎨ × K P r [ ψ = l ] , (CS), kj k = k=1 ⎪ ni −1 Ii ⎪ ⎪ ⎪ li =0 P r Si ≥ δi − li ψij = li P r [ ψij = li ] , ⎪ ⎪ ⎪ ⎪ ⎪ (DCP), ⎪ ⎪ ⎪ ⎪ ngi −1 ⎪ Ii ⎪ ψ P r ≥ δ − l = l ψij = li ] , ⎪ i i ij i Pr [ li =0 Si ⎪ ⎪ ⎪ ⎩ (DCGP), ⎧n −1 nK 1 ⎪ ... nlii=0 ... lK =0 ⎪ l 1 =0 ⎪ ⎪ ni −1 l ⎪ δ −μ ⎪ i i ⎪ Q ti i (1 − ti )ni −1−li ⎪ σi li ⎪ ⎪ ⎪ nk l K ⎪ nk −lk ⎪ k , (CS), ⎨ × k=1,k =i lktk (1 − tk ) = ni −1 ⎪ li =0 Q δi σ−μi nil−1 ti li (1 − ti )ni −1−li , (DCP), ⎪ i i ⎪ ⎪ ⎪ ⎪ l ⎪ n −1 gi δi −μi ngi −1 ⎪ ⎪ ti i (1 − ti )ngi −1−li , ⎪ li =0 Q σi li ⎪ ⎪ ⎪ ⎩ (DCGP), (20) where

999

n 1 =5 for CS

Sim-Class 1 outage prob. for DCGP w/o ici Sim-Class 1 outage prob. for DCP w/o ici Sim-Class 1 outage prob. for CS w/o ici

1.E-03

ici: intercell interference

1.E-04 0

4

8

12

16

20

24

Number of class 1 (2) users, n 1 (n 2 )

Fig. 5. Class 1 outage probabilities of CS, DCP and DCGP without intercell interference for Nc =20.

(22)

The results in this section are also applicable to a random carrier-hopping policy [12] where the subcarriers to use for transmission are randomly selected within the allocated/usable set of subcarriers according to the subcarrier allocation schemes of CS, DCP and DCGP. The effect of multipath fading, which is not the focus of this paper, on the DCGP, DCP and CS schemes could be addressed using techniques similar to those discussed in [24]. VI. N UMERICAL R ESULTS In this section, we present results for the system capacity of the uplink with 2 traffic classes as illustrative examples. The parameter values used in the numerical examples are 2 2 2 , σ22 and σ33 for the tabulated in Table 1. Note that μ11 , σ11

DCP scheme can be obtained dynamically using the above parameters together with equations (12) and (13). With these parameter values, we can express μi and σi as functions of the doublet (n1 ,n2 ). The simulation results presented in this section are obtained using Monte Carlo simulations. The simulation results for outage probabilities presented in Figs. 5-8 are obtained using two runs, and the confidence intervals for the simulation points are obtained using a 90% t-distribution. The number of experiments of each simulation has been chosen to be a large value of 1 million so that most of the percentages of the confidence interval relative to the mean values are within 10%. The cellular network considered consists of 61 hexagonal cells arranged in 4 tiers, surrounding the reference cell. The outage probabilities of classes 1 and 2 for CS, DCP and DCGP with and without intercell intereference for Nc = 20 are shown in Figs. 5, 6, 7 and 8, respectively. The agreements between analytical and simulation results with and without inter-cell interference for these schemes are reasonable.

1000

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 6, NO. 3, MARCH 2007 1.E-01

N g2 =3 n 1 =5 for CS

Sim-Class 2 outage prob. for DCGP w/o ici Sim-Class 2 outage prob. for DCP w/o ici Sim-Class 2 outage prob. for CS w/o ici

1.E-03

ici: intercell interference

1.E-04 0

4

8

12

16

20

n 1 =5 for CS

Sim-Class 2 outage prob. for CS with ici

1.E-03

24

ici: intercell interference 0

Anal-Class 1 outage prob. for CS with ici Sim-Class 1 outage prob. for DCGP with ici Sim-Class 1 outage prob. for DCP with ici Sim-Class 1 outage prob. for CS with ici

1.E-03

ici: intercell interference 12

16

20

n2

N g2 =3

14

12

16

20

24

Number of class 1 (2) users, n 1 (n 2 )

24

N c =20 N c2 =N c -N c1

10

Fig. 7. Class 1 outage probabilities of CS, DCP and DCGP with intercell interference for Nc =20.

From Fig. 6, the number of users for CS without intercell interference is more than that of DCP at an outage probability of 10−3 . On the other hand, from Figs. 7 and 8, the number of users for DCGP with intercell interference is larger than that of DCP which in turn is larger than that of CS at an outage probability of 10−3 for both classes. Note that in determining the system capacity, the outage probabilitity constraints of both classes must be satisfied. The admissible region for the uplink system capacity with Nc = 20, 40 and 60 are shown in Figs. 9, 10 and 11, respectively. The figures show that the uplink capacities, (n1 ,n2 ), of the system with these numbers of subcarriers are on some curves, i.e., the elements of the doublet (n1 ,n2 ) are bounded by these curves. Thus the combinations of the numbers of users of different classes that can be admitted to the system are possible only when these numbers are on or below these curves. Note that Nc1 , Nc2 and Nc3 are in multiples of 4 in the DCP and DCGP schemes. Note also that, in the DCGP scheme, the number of groups of subcarriers for class 1 is Ng1 =Nc1 /4 and the number of groups of subcarriers for class 2 is Ng2 =(Nc -Nc1 )/4. The system capacity decreases when the number of subcarriers increases because the outage probabilities are higher with a larger number of subcarriers. This is due to the decrease in spread-spectrum bandwidth as the number of subcarriers increases, while the overall spreadspectrum bandwidth, W, remains constant. The system capacities for Nc = 20 are larger than those for

N c1 =4

12

Number of class 2 users,

Pr[BER1 >BER*1 ]

N g1 =2

Anal-Class 1 outage prob. for DCP with ici

n 1 =5 for CS

8

8

Fig. 8. Class 2 outage probabilities of CS, DCP and DCGP with intercell interference for Nc =20.

Anal-Class 1 outage prob. for DCGP with ici

N c =20 N c1 =8

4

4

Number of class 2 users, n 2

1.E-01

0

Sim-Class 2 outage prob. for DCGP with ici Sim-Class 2 outage prob. for DCP with ici

1.E-04

Fig. 6. Class 2 outage probabilities of CS, DCP and DCGP without intercell interference for Nc =20.

1.E-04

Anal-Class 2 outage prob. for CS with ici

N g2 =3

1.E-02

Number of class 2 users, n 2

1.E-02

Anal-Class 2 outage prob. for DCP with ici

N g1 =2 Pr[BER2 >BER*2 ]

Pr[BER2 >BER*2 ]

Anal-Class 2 outage prob. for CS w/o ici

Anal-Class 2 outage prob. for DCGP with ici

N c =20 N c1 =8

Anal-Class 2 outage prob. for DCP w/o ici

N g1 =2 1.E-02

1.E-01

Anal-Class 2 outage prob. for DCGP w/o ici

N c =20 N c1 =8

8

N c1 =8 N c1 =4

Complete Sharing

N c1 =12

6

Dynamic Complete Group Partitioning Dynamic Complete Partitioning

4 N c1 =16

N c1 =16

2 0 0

10

20

30

Nu m b er of clas s 1 us er s, n 1 Fig. 9.

System capacity of CS, DCP and DCGP with Nc =20

Nc = 40, and they are larger than those for Nc = 60. Figs. 9, 10 and 11 also show that the system capacities, (n1 ,n2 ,n3 ), of DCP can be larger than those of CS, while the system capacity of DCGP can be larger than those of CS and DCP, with these numbers of subcarriers. Note that by using the DCP scheme for allocation of subcarriers to different classes, the probability that an active spreading code in a subcarrier is used by source i, ti , is increased by having a smaller number of subcarriers to use, i.e., Nci < Nc , (see equation (5)). However, this is significantly offset by eliminating the intra- and inter-cell interference from other classes in its own subcarriers. Similarly, by using the DCGP scheme for allocation of subcarriers to different classes the probability that an active spreading code in a subcarrier is used by source i, ti , is increased by having a smaller number of subcarriers to use, i.e., Zi = Mi + Xi ≤ Nci < Nc , (see equation (5)). However, this is significantly offset by eliminating the intraand inter-cell interference from other classes and some of these interferences from its own class in the other groups in its own group of subcarriers. In a similar way, numerical results can be obtained for any value of K, with the system capacity plotted in a K-dimensional space. Any combination of (n1 ,...,nK ) is admissible as long as it is within the system capacity bound.


10 n2

N c2 =N c -N c1

8 7


N c =40

N c1 =4

9

N c1 =4

6

N c1 =20

5

Dynamic Complete Group Partitioning Dynamic Complete Partitioning Complete Sharing

4 3 2

N c1 =36

1

N c1 =36

1001

partitioning and dynamic complete group partitioning schemes for the allocation of subcarriers for different classes are applied. The numerical examples in Section VI show that the system capacity for DCP is larger that that for CS at these bandwidths, and the system capacity for DCGP is larger than those for DCP and CS. Numerical computation can be used to obtain capacity regions for any number of traffic classes in the uplink. With the expectation of at least ten times more bandwidth than in 3G mobile systems, 4G mobile systems will be able to support more than four types of connections. The analyses here can be used to determine the uplink system capacities for 4G mobile systems.

0 0

5

10

15

ACKNOWLEDGMENT

20

Nu m b er of clas s 1 us ers, n 1 Fig. 10.


n2

16

N c =60

N c1 =4

14

N c2 =N c -N c1


12 10

Complete Sharing

N c1 =28

8 6

Dynamic Complete Group Partitioning Dynamic Complete Partitioning

N c1 =4

4 2

N c1 =56

0 0

5

10

N c1 =56 15

Nu m b er of clas s 1 us ers, n 1 Fig. 11.


VII. C ONCLUDIND R EMARKS We have described a round-robin carrier-hopping multi-rate MC-DS-CDMA approach based on the concept of uniformly distributing the energy of the video source across the Nc subcarriers used for a complete sharing scheme, across the Nci < Nc subcarriers used for a dynamic complete partitioning scheme and across the Mi + Xi ≤ Nci subcarriers used for a dynamic complete group partitioning scheme. Of interest is the capacity region that governs multi-rate multiclass traffic transmissions in the uplink. With the capacity defined as the largest number of users in each traffic class, we have derived the capacity region via an outage probability formulation, and treated the general case where different traffic classes have different spreading gains and each user has the same spreading code across multiple subcarriers. The uplink capacities of three classes with the number of subcarriers at 20, 40 and 60 are presented as illustrative numerical examples in Section VI, which show that the capacities at these bandwidths are on some curves. Complete sharing, dynamic complete

The authors would like to thank the anonymous reviewers for their constructive comments that helped to improve the paper. R EFERENCES [1] K. S. Gilhousen et al., “On the Capacity of a Cellular CDMA System,” IEEE Trans. Vehic. Technol., vol. 40, no. 2, pp. 303-312, May 1991. [2] D. Ayyagari and A. Ephremides, “Cellular Multi-code CDMA Capacity for Integrated (Voice and Data) Services,” IEEE J. Select. Areas Commun., vol. 17, no. 5, pp. 928-938, May 1999. [3] R. Vannithamby and E. S. Sousa, “Performance of Multi-rate Data Traffic using Variable Spreading Gain in the Reverse Link under Wideband CDMA,” IEEE Vehic. Technol. Conf., Conference Record, pp. 1155-1159, 2000. [4] T. C. Wong et al., “Performance Analysis of Multi-class Services in the Uplink of Wideband CDMA,” IEEE Int’l. Conf. Commun. Systems, Conference Record, pp. 692-696, Nov. 2002. [5] P. Sen et al., “odels for Packet Switching of Variable-Bit-Rate Video Source,” IEEE J. Select. Areas Commun., vol. 7, no. 5, pp. 865-869, June 1989. [6] R. O. Onvural, Asynchronous Transfer Mode Networks: Performance Issues. Artech House, 1993. [7] N. Ohta, Packet Video Modeling and Signal Processing. Artech House, 1994. [8] B. Maglaris et al., “Performance Models of Statistical Multiplexing in Packet Video Communications,” IEEE Trans. Commun., vol. 36, no. 7, pp. 834-844, July 1988. [9] T. C. Wong et al., “Performance Analysis of Variable Bit Rate Multiclass Services in the Uplink of Wideband CDMA,” IEEE Int’l. Conf. Commun., Conference Record, pp. 363-367, May 2003. [10] T. C. Wong, J. W. Mark and K. C. Chua, “Performance Evaluation of Video Services in a Multi-rate DS-CDMA System,” IEEE Int’l. Symp. Personal, Indoor, and Mobile Radio Communications, Conference Record, pp. 1490-1495, Sept. 2003. [11] M. K. Simon and M.-S. Alouini, Digital Communication over Fading Channels: A Unified Approach to Performance Analysis. John Wiley and Sons, 2000. [12] T. C. Wong, J. W. Mark and K. C. Chua, “Analytical Modeling of Variable Bit Rate Multi-class Services in a Cellular Random CarrierHopping Multi-rate Multi-Carrier DS-CDMA System by Leaky Buckets,” IEEE Vehic. Technol. Conf. 2004 - Spring, Conference Record, pp. 334-338, 17-19 May 2004. [13] S. Kondo and L. B. Milstein, “Performance of Multi-carrier DS CDMA System,” IEEE Trans. Commun., vol. 44, no. 2, pp. 238-246, Feb. 1996. [14] S. Hara and R. Prasad, “Overview of Multi-carrier CDMA,” IEEE Commun. Mag., vol. 35, no. 12, Dec. 1997. [15] N. Yee, J.-P. Linnartz, and G. Fettweis, “Multicarrier CDMA in Indoor Wireless Radio Networks,” IEEE Int’l. Symp. Personal, Indoor and Mobile Radio Commun., Conference Record, pp. 109-113, Sept. 1993. [16] K. Fazel and L. Papke, “On the performance of Convolutionally-Coded CDMA/OFDM for Mobile Communication System,” IEEE Int’l. Symp. Personal, Indoor and Mobile Radio Commun., Conference Record, pp. 468-472, Sept. 1993. [17] A. Chouly, A. Brajal, and S. Jourdan, “Orthogonal Multicarrier Techniques Applied to Direct Sequence Spread Spectrum CDMA Systems,” IEEE Globecom, Conference Record, pp. 1723-1728, Nov. 1993.

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[18] V. M. DaSilva and E. S. Sousa, “Performance of Orthogonal CDMA Codes for Quasi-Synchronous Communication Systems,” IEEE ICUPC 1993, Conference Record, pp. 995-999, Oct. 1993. [19] L. Vandendorpe, “Multitone Direct Sequence CDMA System in an Indoor Wireless Environment,” IEEE 1st Symp. Communications and Vehic. Technol. in the Benelex, Conference Record, pp. 4.1-1-4.1-8, Oct. 1993 [20] Q. Chen, E. S. Sousa, and S. Pasupathy, “Multi-Carrier DS-CDMA with Adaptive Sub-Carrier Hopping for Fading Channels,” IEEE Int’l. Symp. Personal, Indoor and Mobile Radio Commun., Conference Record, pp. 76-80, Sept. 1995. [21] E. A. Sourour and M. Nakagawa, ”Performance of Orthogonal Multicarrier CDMA in a Multipath Fading Channel,” IEEE Trans. Commun., vol. 44, no. 3, pp. 356-367, Mar. 1996. [22] E. S. Sousa, “The Effect of Clock and Carrier Frequency Offsets on the Performance of a Direct-Sequence Spread-Spectrum Multiple-Access System,” IEEE J. Select. Area Commun., vol. 8, no. 4, pp. 580-587, May 1990. [23] C. Fischione, F. Graziosi, and F. Santucci, “Outage Performance of Power Controlled DS-CDMA Wireless Systems with Heterogeneous Traffic Sources,” Wireless Pers. Commun., vol. 24, no. 2, pp. 171-187, Feb. 2003. [24] B. Hashem and E. S. Sousa, “Reverse Link Capacity and Interference Statistics of a Fixed-Step Power-Controlled DS/CDMA System Under Slow Multipath Fading,” IEEE Trans. Commun., vol. 47, no. 12, pp. 1905-1912, Dec. 1999. David Tung Chong Wong (S’90-M’95-SM’03) received the B.Eng. and M.Eng. degrees from National University of Singapore (NUS) in 1992 and 1994, respectively, and the Ph.D. degree from the University of Waterloo, Canada, in 1999, all in electrical engineering. He is with the Institute for Infocomm Research, Singapore (formerly Centre for Wireless Communications, NUS and Institute for Communications Research, NUS) first as a research engineer and currently as a scientist, since 1994. His research interests are in communications networks, 3G/4G and ultra-wideband wireless mobile multimedia networks. His areas of research are in the medium access control, resource allocation with quality of service constraints, traffic policing with heterogeneous traffic and cross-layer design. Dr. Wong is a Senior Member of IEEE. He was on the Technical Program Committee of the IEEE WCNC 2003, IEEE WCNC 2005, IEEE GLOBECOM 2005 and ICCS 2006. Jon W. Mark (M’62-SM’80-F’88-LF’03) received the B.A.Sc. degree from the University of Toronto in 1962, and the M.Eng. and Ph.D. degrees from McMaster University in 1968 and 1970, respectively, all in electrical engineering. From 1962 to 1970, he was an engineer and then a senior engineer at Canadian Westinghouse Co. Ltd., Hamilton, Ontario, Canada. In September 1970 he joined the Department of Electrical and Computer Engineering,

University of Waterloo, Waterloo, Ontario, where he is currently a Distinguished Professor Emeritus. He served as the Department Chairman during the period July 1984-June 1990. In 1996 he established the Centre for Wireless Communications (CWC) at the University of Waterloo and is currently serving as its founding Director. Dr. Mark had been on sabbatical leave at the following places: IBM Thomas J. Watson Research Center, Yorktown Heights, NY, as a Visiting Research Scientist (1976-77); AT&T Bell Laboratories, Murray Hill, NJ, as a Resident Consultant (1982-83): Laboratoire MASI, Universit´e Pierre et Marie Curie, Paris France, as an Invited Professor (1990-91); and Department of Electrical Engineering, National University of Singapore, as a Visiting Professor (1994-95). He has previously worked in the areas of adaptive equalization, image and video coding, spread spectrum communications, computer communication networks, ATM switch design and traffic management. His current research interests are in broadband wireless communications, resource and mobility management, and cross domain interworking. He is a co-author of the text entitled Wireless Communications and Networking, Prentice-Hall 2003. A Life Fellow of IEEE, Dr. Mark is the recipient of the 2000 Canadian Award for Telecommunications Research and the 2000 Award of Merit of the Education Foundation of the Federation of Chinese Canadian Professionals. He was an editor of IEEE Transactions on Communications (1983-1990), a member of the Inter-Society Steering Committee of the IEEE/ACM Transactions on Networking (1992-2003), a member of the IEEE Communications Society Awards Committee (1995-1998), an editor of Wireless Networks (1993-2004), and an associate editor of Telecommunication Systems (19942004). Kee Chaing (KC) Chua (M’87) received a PhD degree in Electrical Engineering from the University of Auckland, New Zealand in 1990. He joined the National University of Singapore (NUS) as a Lecturer in 1990 and is now a Professor in the Department of Electrical & Computer Engineering. He served as the Faculty of Engineering’s Vice Dean for Research from June 2003 to March 2006. From 1995 to 2000, he was seconded to the Center for Wireless Communications (now part of the Institute for Infocomm Research), a national telecommunication R&D centre funded by the Singapore Agency for Science, Technology and Research as its Deputy Director. From 2001 to 2003, he was on leave of absence from NUS to work at Siemens Singapore where he was the founding head of the Mobile Core R&D Department funded by Siemens’ ICM Group. Since March 2006, he has been seconded to the National Research Foundation as a Director. Dr Chua has carried out research in various areas of communication networks and has published more than 180 papers in these areas in international refereed journals and conferences. His current research interests are in wireless networks (in particular wireless sensor networks) and optical burst switched networks. He has also been an active member of the Institute of Electrical & Electronics Engineers (IEEE), Inc., and is a recipient of an IEEE 3rd Millennium medal.