Device-to-device (D2D) communication has great potential to improve spectrum efficiency and offload traffic for cellular networks. In this paper, we focus on a multiflow two-way D2D network with decode-and-forward (DF) relays, coexisting with OFDMA cellular network. The spectrum sharing and relay selection are considered to minimize the outage probability of the device in D2D networks. The induced problem is a complicated probabilistic integral programming. A novel weighted random bipartite graph (WRBG)-based minimum weight maximum matching (MWMM) approach will be proposed in this paper. To offload not only the traffic but also the signaling and computation overhead, the improved min-sum algorithm will be applied to find the MWMM in the distributed manner with only polynomial complexity. The proposed approach enjoys an advantage that the close-form approximation formulas for optimal outage probability and diversity-multiplexing tradeoff can be derived by analyzing the properties of MWMM on WRBG. Both the theoretical derivations and simulation results will illustrate that the proposed approach for multiflow two-way D2D networks achieves the same performance as single-flow two-way D2D systems. Therefore, the distributed WRBG matching approach yields not only a practical distributed algorithm, but also a simple and elegant theoretical framework for multiflow two-way D2D networks.

The green communications, which focus on improving the energy efficiency, have attracted much attention from both academia and industry recently. In this paper, the tradeoff between outage probability and energy efficiency will be addressed for multi-flow cooperative communication systems with taking energy budget and devices energy consumption into consideration. The proposed approach will first formulate the multi-flow cooperative communication system as a weighted random bipartite graph (WRBG) model. The minimum weighted maximum matching (MWMM) method will then be proposed to select a relay for each source-destination (s-d) pair in order to minimize the outage probability and maximize the average energy efficiency simultaneously. By analyzing the properties of every sample of the WRBG model, the closed-form formulas for the outage probability and average energy efficiency will then be obtained. Therefore, based on the derived tradeoff, the outage probability and average energy efficiency can be balanced by adjusting the energy budgets and transmission rate according to the system requirement. Moreover, the proposed MWMM method also enjoys an advantage of the log-polynomial computation complexity for parallel implementations.

Power allocation is an important issue for spectrum sharing of unlicensed bands, in which multiple unlicensed systems may coexist and operate. Some recent works have been reported on spectrum sharing in frequency-flat FF unlicensed bands. However, there has not been much work on power allocation for spectrum sharing in frequency-selective FS unlicensed bands. For multiple cooperative systems cooperating on FS interference channels ICs, we study an optimal power allocation strategy, which allows the transmission power density to vary within one subcarrier. By showing the duality of FS and parallel FF channels, we can therefore compute the achievable rate region of the proposed strategy when systems cooperate with each other. For non-cooperative scenarios, we construct a game-theoretical framework for multiple selfish systems on FS ICs. This framework enables us to utilize existing protocols designed for FF ICs to FS scenarios. By numerical results, in both cooperative and non-cooperative scenarios, we show that the proposed strategy achieves a larger rate region than a conventional strategy, where the transmission power density on each subcarrier is set equal. Our work can be regarded as an extension of previous works for FF scenarios. Copyright © 2012 John Wiley & Sons, Ltd.

The channel state information at the transmitter side (CSIT) is playing a more and more important role in the design of OFDM/OFDMA communication systems. Unfortunately, it is not trivial to conduct a performance analysis of OFDM systems with partial CSIT. Using the saddle-point approximation method, this paper will develop an analytical design and performance analysis framework for OFDM channels with 1 bit CSIT, which we shall refer to as the conditional outage exponent. The proposed framework will then allow us to present the fundamental relationship among the outage probability, transmission rate, SNR, outage capacity, delay-limited capacity, ergodic capacity, diversity-multiplexing tradeoff (DMT), finite-SNR DMT, and the number of diversity branches. It is surprising that the outage performance with 1 bit CSIT (conditional outage exponent) is worse than the corresponding one without CSIT (non-conditional outage exponent) in most cases. This counter-intuitive phenomenon occurs because the observation of the channel at the transmitter side will result in a state space collapse of the channel gains, i.e., from the prior probability space to the posterior probability space. As a result, the conditional outage exponent based framework can be easily used to design and evaluate the performance of existing and upcoming OFDM/OFDMA multichannel systems with 1 bit CSIT.

Cooperative transmission in vehicular networks is studied by using coalitional game and pricing in this paper. There are several vehicles and roadside units (RSUs) in the networks. Each vehicle has a desire to transmit with a certain probability, which represents its data burtiness. The RSUs can enhance the vehicles' transmissions by cooperatively relaying the vehicles' data. We consider two kinds of cooperations: cooperation among the vehicles and cooperation between the vehicle and RSU. First, vehicles cooperate to avoid interfering transmissions by scheduling the transmissions of the vehicles in each coalition. Second, a RSU can join some coalition to cooperate the transmissions of the vehicles in that coalition. Moreover, due to the mobility of the vehicles, we introduce the notion of encounter between the vehicle and RSU to indicate the availability of the relay in space. To stimulate the RSU's cooperative relaying for the vehicles, the pricing mechanism is applied. A non-transferable utility (NTU) game is developed to analyze the behaviors of the vehicles and RSUs. The stability of the formulated game is studied. Finally, we present and discuss the numerical results for the 2-vehicle and 2-RSU scenario, and the numerical results verify the theoretical analysis.

In this paper, we consider the power allocation of the physical layer and the buffer delay of the upper application layer in energy harvesting green networks. We analyze the delay-optimal power allocation problem over fading channels. The total power required for reliable transmission includes the transmission power as well as the circuit power. The harvested power (which is stored in a battery) and the grid power constitute the power resource. The objective is to find a policy to minimize the buffer delay under the constraint on the average grid power. The policy is a two-dimensional vector with the transmission rate and the power allocation of the battery as its elements. In each transmission, the transmitter decides the transmission rate and the allocated power from the battery (the rest of the required power will be supplied by the power grid). A constrained Markov decision process (MDP) problem is formulated when the data arrival process, the harvested energy arrival process, and the channel process are Markov processes. We prove that the optimal policy can be obtained as follows. First, we solve the optimal rate through a reduced MDP problem that is only related to the average harvested energy but not the harvested energy arrival process. Second, the battery's power allocation can be given based on the optimal rate. By analyzing the reduced MDP problem through the transformations to the average cost MDP and discount optimal MDP, we derive some structural properties of the optimal policy. Moreover, the closed-form expression is obtained for the independent and identically distributed (i.i.d.) cases.

Owing to the capability of accumulating mutual information from the transmission of previous nodes, rateless codes can boost the network performance considerably, and hence have sparked much interest recently. However, how to efficiently schedule multi-hop multi-relay transmissions with the aid of rateless codes remains a challenging work. Particularly, it requires high complexity to find an optimal route due to its inherent combinatorial nature. In this paper, we formulate the optimal transmission scheduling as a dynamic programming (DP) problem by defining a novel state and constructing a tree-structured state transition diagram. It is from a point of view of DP that we further propose two low-complexity algorithms, namely S-DIRAC and Fano-DIRAC, with negligible performance loss based on the idea of sequential decoding of convolutional codes. Simulation results indicate that the low-complexity algorithms almost always find the optimal solution and show the superiority of routing with mutual information accumulation compared to conventional shortest path routing.

Network coding (NC) compresses two traffic flows with the aid of low‐complexity algebraic operations, hence holds the potential of significantly improving both the efficiency of wireless two‐way relaying, where each receiver is collocated with a transmitter and hence has prior knowledge of the message intended for the distant receiver. In this contribution, network coded modulation (NCM) is proposed for jointly performing NC and modulation. As in classic coded modulation, the Euclidean distance between the symbols is maximised, hence the symbol error probability is minimised. Specifically, the authors first propose set‐partitioning‐based NCM as an universal concept which can be combined with arbitrary constellations. Then the authors conceive practical phase‐shift keying/quadrature amplitude modulation (PSK/QAM) NCM schemes, referred to as network coded PSK/QAM, based on modulo addition of the normalised phase/amplitude. To achieve a spatial diversity gain at a low complexity, a NC oriented maximum ratio combining scheme is proposed for combining the network coded signal and the original signal of the source. An adaptive NCM is also proposed to maximise the throughput while guaranteeing a target bit error probability (BEP). Both theoretical performance analysis and simulations demonstrate that the proposed NCM can achieve at least 3 dB signal‐to‐noise ratio gain and two times diversity gain.

The parallel fading channel, which consists of finite number of subchannels, is very important, because it can be used to formulate many practical communication systems. The outage probability, on the other hand, is widely used to analyze the relationship among the communication efficiency, reliability, signal-to-noise ratio (SNR), and channel fading. To the best of our knowledge, the previous works only studied the asymptotic outage performance of the parallel fading channels which are only valid for a large number of subchannels or high SNRs. In this paper, a unified performance metric, which we shall refer to as the outage exponent, will be proposed. Our approach is mainly based on the large deviations theory and Meijer'sG-function. It is shown that the proposed outage exponent is not only an accurate estimation of the outage probability for any number of subchannels, any SNR, and any target transmission rate, but also provides an easy way to compute the outage capacity, finite-SNR diversity-multiplexing tradeoff, and SNR gain. The asymptotic performance metrics, such as the delay-limited capacity, ergodic capacity, and diversity-multiplexing tradeoff can be directly obtained by letting the number of subchannels or SNR tend to infinity. Similar to Gallager's error exponent, a reliable function for parallel fading channels, which illustrates a fundamental relationship between the transmission reliability and efficiency, can also be defined from the outage exponent. Therefore, the proposed outage exponent provides a complete and comprehensive performance measure for parallel fading channels.

Multicast/broadcast is regarded as an efficient technique for wireless cellular networks to transmit a large volume of common data to multiple mobile users simultaneously. To guarantee the quality of service for each mobile user in such single-hop multicasting, the base-station transmitter usually adapts its data rate to the worst channel condition among all users in a multicast group. On one hand, increasing the number of users in a multicast group leads to a more efficient utilization of spectrum bandwidth, as users in the same group can be served together. On the other hand, too many users in a group may lead to unacceptably low data rate at which the base station can transmit. Hence, a natural question that arises is how to efficiently and fairly transmit to a large number of users requiring the same message. This paper endeavors to answer this question by studying the problem of multicasting over multicarriers in wireless orthogonal frequency division multiplexing (OFDM) cellular systems. Using a unified utility maximization framework, we investigate this problem in two typical scenarios: namely, when users experience roughly equal path losses and when they experience different path losses, respectively. Through theoretical analysis, we obtain optimal multicast schemes satisfying various throughput-fairness requirements in these two cases. In particular, we show that the conventional multicast scheme is optimal in the equal-path-loss case regardless of the utility function adopted. When users experience different path losses, the group multicast scheme, which divides the users almost equally into many multicast groups and multicasts to different groups of users over nonoverlapping subcarriers, is optimal .

In wireless cellular systems, it is an important and challenging task to reliably multicast to numerous users that require the same contents at one transmission. In this paper, we propose a network coding based multicast scheme for wireless cellular OFDM systems. The base station encodes source packets with linear network coding and multicasts the coded packets to the target users over multicarriers. Thus, the users can correctly recover the source message as long as they successfully receive a certain number of packets. The reliability of coded wireless multicast is characterized by the user outage probability, which can be greatly reduced by efficiently exploiting frequency diversity gain via network coding. We show that the BS shall adjust the data transmission rate per carrier to strike a good balance between the reliability at each subcarrier and the redundancy among coded packets. It is also found that full diversity gain and no diversity gain should be exploited in the high and low SNR regimes, respectively. Simulation results also reveal that network coding generally provides great advantage for reliable wireless multicasting to a large number of users.

In this paper, a random combinatorial optimization approach, which we shall refer to as random bipartite graph (RBG) based maximum matching, will be proposed to investigate and solve the joint relay selection and subchannel allocation problem in cooperative networks. By studying the properties of the maximum matching on RBG, the outage probability and diversity-multiplexing tradeoff of the proposed RBG matching method will be obtained. It will then be demonstrated that the outage probability and diversity-multiplexing tradeoff of the RBG matching method for cooperative communication systems with multiple source-destination pairs is the same as that of relay systems with only one source and one destination, i.e., d(r) = N (K + 1)(1 - 2r), where N is the number of subchannels, and K is the number of relay nodes. In addition, it will be shown that the proposed algorithm for maximum matching enjoys a sublinear computation complexity O(N2/3). Simulation results will illustrate the potential of the proposed RBG matching method as well as verify the theoretical derivations.

Automatic Repeat reQuest (ARQ) and Rateless Coding (RC) are two major feedback-based error control schemes. However, due to the lack of common metrics for measuring the performance, ARQ and RC have not been systematically compared yet. In this paper, we establish a unified analytical framework based on two novel metrics, namely forward redundancy and feedback redundancy, and present a comparative study on ARQ and RC from the point of view of redundancy. In particular, we conduct a fair comparison of both schemes over point-to-point fading channels and broadcast fading channels. The comparison indicates that RC is capable of beating ARQ completely at low signal-to-noise ratios in broadcast communications. In other cases, neither of them could dominate the other. Therefore, we propose a selection method to determine which scheme to employ with given system parameters.

The authors propose a cross-layer approach, which exploits distributed beamforming in the physical layer and token passing in the media access control (MAC) layer, to improve quality of service (QoS) for secondary users (SUs) with bursty traffics in cognitive relay systems. In this scheme, source-to-destination transmissions are relayed by some SU nodes, which can form a distributed beamformer to forward messages in busy timeslots while completely eliminating interference to primary users (PUs). In contrast with previous cognitive relaying protocols, this scheme can utilise more spectrum resources, namely idle timeslots (or temporal spectrum holes) as well as busy timeslots (or spatial spectrum holes). Based on a token passing mechanism, an opportunistic scheduling protocol is then developed to dynamically balance available spectrum holes between the source and the relays, and hence adapts to bursty arrival of secondary traffics and random presence of PUs. By formulating a tandem queueing analytical framework, the performance of the proposed scheme is then analysed using a multi-dimensional Markov chain model. Numerical results demonstrate that the proposed scheme can achieve significant QoS gains over conventional cognitive relaying protocols that utilise only idle timeslots.

Cognitive radio (CR) provides a promising solution to the spectrum scarcity problem by implementing opportunistic spectrum access over the licensed spectrum. However, spectrum holes are discontinuous in frequency and time, resulting in a challenge to CR transmissions. Fortunately, rateless codes can be utilised to exploit these distributed spectrum opportunities in an aggregate way. In such system, how to conduct the sensing and transmission is a key problem that affects the system performance. Therefore in this study, the authors propose a rateless-coded transmission protocol in a multi-channel CR system, addressing the media access control (MAC) layer sensing issues. Specifically, how many channels and which ones should be sensed in each time slot. Owing to the dynamics of channel availability, stochastic control is a necessity. Therefore the authors analyse the average throughput and formulate an optimisation problem to find the optimal sensing policy based on the theory of partially observable Markov decision process (POMDP). The myopic sensing policy is also studied owing to intractable computation complexity of a general POMPD. Moreover, the authors propose a heuristic policy with comparable performance and low complexity. Simulation results will show that the heuristic policy is superior to the static policy and has almost the same performance as the myopic policy.

In multirate digital signal processing, cosine-modulated filter banks (CMFB) satisfying perfect reconstruction (PR) or near-perfect reconstruction (NPR) property are of great interest owing to their extensive applications in data compression, feature detection and extraction and signal transmultiplexing. And the key to PR CMFB design is to design a PR prototype filter (PF). However, designing optimal PR and NPR PF is essentially a constrained non-linear programming. It is generally modelled as a non-convex quadratically constrained quadratic optimisation problem. So far, this kind of optimisation is still a very difficult class of optimisation and no practical but few metaheuristic algorithm is availabe for finding its global optimal solution. The study proposed a two-stage method for designing PR PF. In the first stage, a metaheuristic algorithm based on variable neighbourhood search is proposed for designing lower-ordered PR PF, that is the corresponding PR CMFB has less channels. Then a least-mean-square error approach is introduced to increase the length of the designed lower-ordered PF with the PR property unchanged. Design examples are given to illustrate the proposed algorithm outperforms the existing one in reconstruction error and stopband attenuation.

Recent works have shown that cooperative diversity can be achieved by using relay selection (RS), distributed space-time coding (DSTC), and distributed beam-forming (DBF) in narrow-band decode-and-forward (DF) cooperative networks with one source-and-destination (s-d) pair. However, the joint resource allocation for broadband DF cooperative networks with multiple s-d flows has not received much attention yet. In this paper, a random hypergraph based unified matching framework is proposed, under which five feasible types of multi-flow DF cooperative networks will be considered. In each type, the maximum matching method will be applied to RS, DSTC, and DBF schemes so as to achieve the optimal channel allocation and relay selection with fairness assurance. By analyzing the properties of maximum matching, the outage probability of each s-d pair after resource allocation will be obtained. The results of diversity-multiplexing tradeoff will show that the proposed framework is capable of achieving the full frequency diversity and cooperative diversity for each s-d pair simultaneously, while the frequency multiplexing is equally shared. Based on the unified framework, the random rotation based parallel Hopcroft-Karp (R2PHK) algorithm will then be designed, which can work in each destination node independently, and shall enjoy a poly-logarithmic complexity O(log2loN), where N is the number of channels and lois a constant.

Cognitive Radio (CR) can significantly improve the utilization of the precious radio spectrum by allowing Secondary Users (SUs) to borrow the licensed spectrum if they do not cause harmful interference to Primary Users (PUs). As a wireless technology, CR confronts the challenges of wireless channels inevitably and thus wishes to employ node cooperation to achieve spatial diversity gain. However, conventional cooperative diversity technologies require two idle timeslots for each transmission. This implies two temporal spectrum holes are needed for each transmission when the technologies are applied to CR Networks (CRNs). This can cause severe delay, as temporal spectrum holes are only available from time to time in CRNs. In this paper, we present a cross-layer approach, where cooperative beamforming is adopted to forward messages in busy timeslots without causing interference to PUs, so as to achieve cooperative diversity gain and improve Quality of Service (QoS) for SUs without consuming additional idle timeslots or temporal spectrum holes. In the physical layer, the beamforming weight vector and the cooperative diversity gain are obtained using a geometric approach. The MAC layer of the cooperative communication in CRNs can be modeled by a tandem queue, where the source queue is the bottleneck. Therefore, we propose an optimal opportunistic priority scheduling scheme in the MAC layer, the timeout probability of which is obtained using an absorbing Markov chain. A cross-layer optimization of the transmission rate is then carried out to jointly reduce the timeout and outage probabilities. Its significant QoS gain is demonstrated by simulations.

There have been increasing interests in integrating cooperative diversity into Cognitive Radios (CRs). However, conventional cooperative diversity protocols require at least two randomly available idle timeslots or temporal spectrum holes for one transmission, thus leading to limited throughput and/or large latency. In this paper, we propose a novel cross-layer approach for efficient scheduling in CR systems with bursty secondary traffics. Specifically, cooperative beamforming is exploited for Secondary Users (SUs) to access busy timeslots or spatial spectrum holes without causing interference to primary users. We first propose a basic cooperative beaMforming and Automatic repeat request aided oppoRtunistic speCtrum scHeduling (MARCH) scheme to balance available spectrum resources, namely temporal and spatial spectrum holes, between the source and the relays. To analyze the proposed scheme, we develop a tandem queuing framework, which captures bursty traffic arrival, dynamic availability of spectrum holes, and time-varying channel fading. The stable throughput region and the average delay are characterized using a structured matrix-analytical method. We then obtain delay optimal scheduling schemes for various scenarios by jointly optimizing the scheduling parameters. Finally, we propose a modified scheme, MARCH-IR, which combines MARCH with Incremental Relay selection to further improve the system performance. Simulation results reveal that the proposed schemes provide significant Quality of Service (QoS) gains over conventional scheduling schemes that access only temporal spectrum holes.

Network coding, which can combine various traffic flows or packets via algebraic operations, has the potential of achieving substantial throughput and power efficiency gains in wireless networks. As such, it is considered as a powerful solution to meet the stringent demands and requirements of next-generation wireless systems. However, because of the random and asynchronous packet arrivals, network coding may result in severe delay and packet loss because packets need to wait to be network-coded with each others. To overcome this and guarantee quality of service (QoS), we present a novel cross-layer approach, which we shall refer to as Buffer-Aware Network Coding, or BANC, which allows transmission of some packets without network coding to reduce the packet delay. We shall derive the average delay and power consumption of BANC by presenting a random mapping description of BANC and Markov models of buffer states. A cross-layer optimization problem that minimizes the average delay under a given power constraint is then proposed and analyzed. Its solution will not only demonstrate the fundamental performance limits of BANC in terms of the achievable delay region and delay-power tradeoff, but also obtains the delay-optimal BANC schemes. Simulation results will show that the proposed approach can strike the optimal tradeoff between power efficiency and QoS.

Analog network coding is a promising technique which can greatly improve the transmission efficiency of wireless communications. In two-way relay systems with multiple subchannels, multiple user pairs and multiple relays, however, the optimal joint relay selection and subchannel allocation problem has not been studied in a systematic way. In this paper, a random combinatorial optimization approach, referred to as the weighted random bipartite graph (WRBG) based minimum weighted matching (MWM) method, will be proposed to solve this problem. By analyzing the properties of the MWM on WRBG, we shall derive the outage probability and diversity-multiplexing tradeoff of each user after relay selection and channel allocation. Theoretical results will demonstrate that the outage probability, cooperative diversity, and frequency diversity of the proposed WRBG based MWM method for multi-user two-way relay systems is the same as that of two-way relay systems with only one user pair. The proposed algorithm for MWM also enjoys a low computation complexity of O(log2N) for parallel implementations, where N is the number of subchannels. Simulation results will illustrate the potential of the proposed method and also verify the theoretical derivations.

Due to the broadcast nature of wireless transmissions, overheard signals can be exploited in multi- hop wireless networks so as to improve the network performance. It has been shown that energy accumulation and information accumulation are two main approaches to utilize multiple overheard signals. However, how to jointly accumulate energy and information in multi-hop wireless networks is still unknown. In this paper, we propose a new rateless coded relaying scheme in linear multi-hop wireless networks, where energy and information can be jointly accumulated by superimposing two rateless-coded packets generated from the same information bits using different codebooks. The average end-to-end throughput is analyzed. Furthermore, we formulate an optimization problem to find the optimal power allocation ratio and obtain the least transmission time for relay nodes. Simulation results will show that compared to pure energy accumulation and pure information accumulation, our proposed scheme can achieve much higher throughput.

Relay selection has been shown to be a practical and effective way to achieve cooperative diversity. In wide-band OFDM cooperative communication systems with multiple source and destination nodes, however, the best relay selection and subchannel allocation has not been studied in a systematic way. In this paper, a random combinatorial optimization approach, referred to as the random bipartite graph based maximum matching (RBG matching), will be proposed to solve this problem. By applying the method of Euler beta function and generalized hypergeometric function, we will first derive a new closed-form outage probability for the best relay selection in the decode-and-forward (DF) scheme. Based on this result and the properties of the maximum matching on RBG, the outage probability and diversity-multiplexing tradeoff of the proposed RBG matching method will also be derived. As a result, we will demonstrate that the outage probability and the cooperative and frequency diversity-multiplexing tradeoff of the RBG matching method for cooperative communication systems with multiple source-destination pairs is the same as that of relay systems with only one source and one destination. Besides, the proposed algorithm for maximum matching also enjoys a sublinear computation complexity O(N2/3), where N is the number of subchannels. Simulation results will illustrate the potential of the proposed RBG matching method, and also verify the theoretical derivations.

Cooperative diversity is an emerging and powerful solution that can significantly improve the diversity order and link reliability over the harsh wireless fading channels. Although there has been a lot of work on achieving full diversity by using advanced space-time coding or signal processing schemes, how to increase the spectral efficiency or multiplexing gain with half-duplex relays has not received much attention so far. In this paper, we will present a spectral efficient cooperative diversity method, which adopts our recently proposed Network Interference CancEllation (NICE) to thoroughly mitigate the inter-relay interference in successive relaying, where a source and a relay may send different messages simultaneously. We shall also investigate the optimal diversity multiplexing tradeoff of the proposed method, and show that its diversity gain is strictly greater than that of the two-timeslot relaying protocols for large multiplexing gains. Moreover, the decoding algorithm for the relays and destination has a similar complexity as that of the decision feedback equalizer.

In this paper, we propose an opportunistic scheduling scheme to serve bursty traffics in cognitive radios, where cooperative beamforming is exploited to access busy timeslots or spatial spectrum holes to forward messages without causing interference to primary users. Specifically, based on cooperative beamforming in the physical layer and automatic repeat request for error recovery in the link layer, our proposed scheme strives to balance available spectrum resources, namely temporal and spatial spectrum holes, between the source and the relays so as to greatly reduce the average delay. To analyze the proposed scheme, we then develop a tandem queueing analytical framework, which captures bursty traffic arrival, dynamic availability of spectrum holes, and time-varying channel fading. By modelling it with a multi-dimensional Markov chain, the average delay is derived using a structured matrix-analytical method. Finally, we obtain delay optimal scheduling schemes by jointly optimizing the scheduling parameters. Simulation results reveal that the proposed scheme provides significant quality of service gains over conventional scheduling schemes that access only temporal spectrum holes.

We propose a cooperative beamforming aided incremental relaying scheme to improve spectrum efficiency of cognitive radio systems. In this scheme, the source and relays can utilize cooperative beamforming to activate packet retransmission in busy timeslots or spatial spectrum holes, if the destination fails to receive the packets transmitted from the source. Therefore, cooperative diversity gain is obtained without consuming extra idle timeslots. Given a packet loss constraint, our proposed scheme endeavors to further improve the system throughput by dynamically adjusting the maximum number of retransmissions. We derive the average throughput of the proposed scheme and obtain the maximum throughput by optimizing the scheduling parameters. Theoretical and simulation results reveal that the proposed scheme obtains a significant throughput gain compared to direct transmission as well as conventional incremental relaying schemes utilizing idle timeslots only.

Cooperative communication with rateless codes has attracted much attention recently because it combines spatial diversity of multiple nodes and high bandwidth efficiency of rateless codes. However, relay selection for asynchronous relaying, which shows great potential for practical applications, has not been carefully studied yet. In this paper, based on rateless codes, we propose a simple probabilistic relay selection protocol for asynchronous multi-relay networks, where no symbol-level inter-node synchronization or multiuser detection is needed. In such asynchronous networks, a decoding relay can help the other relays which have not decoded the message yet. Moreover, the tradeoff between the first hop and the second hop can be controlled by setting the decoding relay threshold. We analyze the average end-to-end throughput and find an optimal decoding relay threshold to maximize the throughput. Simulation results show the superiority of the proposed protocol at low Signal-to-Noise Ratios (SNRs) when the relays are close to the source.

In cognitive relay systems, spectrum holes exist in 4 dimensions (4-D), namely, time, frequency, location, and direction. How to efficiently utilize these different kinds of spectrum holes to provide quality-of-service (QoS) guarantees for secondary users (SU) is a challenging task. In this paper, we first identify the benefits of separately applying cooperative beamforming and rateless coding aided relaying technologies. Specifically, cooperative beamforming has the particular advantage of exploiting spatial or directional spectrum holes without causing interference to PUs. On the other hand, rateless coding is capable of utilizing different kinds of spectrum opportunities in an aggregate way with low complexity. Both cooperative beamforming and rateless coding aided cognitive relaying schemes have been proposed to support either elastic or real-time traffics for SUs. Furthermore, we combine cooperative beamforming and rateless coding together in order to provide an efficient and robust way to utilize 4-D spectrum holes in cognitive relay systems, where spectrum sensing and channel estimation may be imperfect. A substantial performance gain can be obtained by the combination, compared to using these two techniques separately.

Spectrum sensing is the first key functionality to realize Cognitive Radios which also meet harsh performance demands under various severe conditions, e.g. the reliability and sensitivity demands under the low sensing overhead constraint. Cooperative sensing exploiting SPRT is an efficient sensing method which can significantly decrease sensing delay and sensing overhead, thereby, has been extensively studied. However, how to implement sequential detection with low signaling complexity and less sensing delay has not been considered yet. In this paper, we proposed an efficient and reliable cooperative sensing scheme where each SU reports their local decisions multiple times before the global decision is made. We will demonstrate that our proposed scheme is capable of not only achieving the high sensing performance but also the low sensing delay and overhead.

Network coding compresses multiple traffic flows with the aid low-complexity algebraic operations, hence holds the potential of significantly improving both the power and bandwidth efficiency of wireless networks. In this contribution, the novel concept of Network Coded Modulation (NCM) is proposed for jointly performing network coding and modulation in bi-directional/duplex relaying. Each receiver is colocated with a transmitter and hence has prior knowledge of the message intended for the distant receiver. As in classic coded modulation, the Euclidian distance between the symbols is maximized, hence the Symbol Error Ratio (SER) is minimized. Specifically, we conceive NCM methods for PSK, PAM and QAM based on modulo addition of the normalized phase or amplitude. Furthermore, we propose low complexity decoding algorithms based on the corresponding conditional minimum distance criteria. Our performance analysis and simulations demonstrate that NCM relying on PSK is capable of achieving a SER at both receivers of the NCM scheme as if the relay transmitted exclusively to a single receiver only. By contrast, when our NCM concept is combined with PAM/QAM, an SNR loss (<;1.25 dB) is imposed at one of the receivers, usually at the one having a lower data rate in a realistic different rate scenario. Finally, we will demonstrate that the proposed NCM is compatible with existing physical layer designs.

Due to the potential of enhancing traffic safety, protecting environment, and enabling new applications, vehicular communications, especially vehicle-to-vehicle (V2V) communications, has recently been receiving much attention. Because of both safety and non-safety real-time applications, V2V communications has QoS requirements on rate, latency, and reliability. How to appropriately design channel allocation is therefore a key MAC/PHY layer issue in vehicular communications. The QoS requirements of real-time V2V communications can be met by achieving a low outage probability and high outage capacity. In this paper, we first formulate the subchannel allocation in V2V communications into a maximum matching problem on random bipartite graphs. A distributed shuffling based Hopcroft-Karp (DSHK) algorithm will then be proposed to solve this problem with a sub-linear complexity of O(N^{2/3}), where N is the number of subchannels. By studying the maximum matching generated by the DSHK algorithm on random bipartite graphs, the outage probabilities are derived in the high (two near vehicles) and low (two far away vehicles) SNR regimes, respectively. It is then demonstrated that the proposed method has a similar outage performance as the scenario of two communicating vehicles occupying N subchannels. By solving high degree algebraic equations, the outage capacity can be obtained to determine the maximum traffic rate given an outage probability constraint. It is also shown that the proposed scheme can take an advantage of small signaling overhead with only one-bit channel state information broadcasting for each subchannel.

OFDMA is a promising technique because it is capable of improving the transmission reliability and efficiency of multi-user wireless communications. However, previous works on the performance of OFDMA did not properly consider the fundamental relationship between multiplexing and diversity in OFDMA systems. As a comprehensive performance metric, the diversity-multiplexing tradeoff will be applied in this paper to evaluate the subcarrier allocation scheme. The OFDMA system will be formulated into a correlated random bipartite graph model, in which, whether the edges occur or not depends on the distribution of the channel fading. The \mathcal{H}-matching method, which is used to determine the maximum collection of vertex-disjoint copies of a fixed sub-graph \mathcal{H} contained in a given graph, will then be developed to address the optimal subcarrier allocation problem. Theoretical analysis will show that the proposed \mathcal{H}-matching method achieves the optimal outage performance at a given target multiplexing gain, which implies that the optimal diversity-multiplexing tradeoff can be achieved by only allocating subcarriers. Although the \mathcal{H}-matching problem is NP-complete, the proposed Random Rotation and Expansion based Hopcroft-Karp (R^2EHK) algorithm can still achieve the asymptotically optimal outage performance (i.e., optimal diversity-multiplexing tradeoff) with a sub-linear complexity. Furthermore, the channel state information needed is only one bit per subcarrier. Simulation results will verify the theoretical analysis and will show that the performance loss of the R^2EHK algorithm is negligible compared to the exhaustive search method. In addition, it is also shown that the R^2EHK algorithm has at least a 2 dB SNR gain compared to the interleaved subcarrier allocation with water-filling power allocation in IEEE 802.16 standards.

OFDM is playing a more and more important role in wireless communication systems. Unfortunately, it is not trivial to conduct a performance analysis of OFDM systems. Therefore, it is highly desired to develop an analytical design and performance analysis framework for OFDM channels. In this paper, we consider a unified performance metric for OFDM channels, which we shall refer to as outage exponent. The outage exponent, which is a special exponentially tight upper bound on outage probabilities, presents the fundamental relationship among the outage probability, target transmission rate, capacity of AWGN channel, SNR, and the number of diversity branches. The SNR gains of different coding schemes and the (finite-SNR and asymptotic) diversity-multiplexing tradeoff can be obtained from the outage exponent directly. In order to calculate the outage exponent for OFDM channels, we shall apply the large deviations theory, which will not only obtain an accurate estimation of the rate function, but also the coefficient of the exponential function. It is shown that the obtained outage exponent can allow the accurate estimation of the additional power required to decrease the outage probability by a specified value. Therefore, the outage exponent can be easily used to design and evaluate the performance of existing and upcoming OFDM systems.

Recent work has shown that distributed (or cooperative) beamforming can achieve cooperative gain, such as throughput gain and diversity gain, with no need for extra spectral holes in Cognitive Wireless Networks (CWNs). However, how to efficiently schedule cooperative beamforming to improve the quality of service of unlicensed secondary users has not been well addressed. In this paper, a simple opportunistic scheduling scheme is proposed to serve delay-sensitive traffics in CWNs with cooperative beamforming. After the probabilities of outages due to channel fading and random appearance of primary users are analyzed, respectively, the overall outage probability of our scheme is minimized by optimizing the scheduling parameter. The optimal scheduling scheme is then derived for the high-SNR regime. Simulation results show that compared to conventional schemes without cooperative beamforming, our scheduling scheme can significantly lower down the probability of message transmission failure within a given time period.

Rateless coding ensures reliability for time-varying channels by providing ever-increasing redundancy at the packet level. However, the optimal packet length for rateless codes has not been carefully studied from the application layer and the physical layer. In this paper, we present a practical wireless communication system consisting of an LT coding module, a channel coding module, and error detection modules. By analyzing the system performance, we find the impacts of packet length on reliability and efficiency, and formulate the optimization problem that maximizes the throughput efficiency over time- varying channels. We also compare the performance of the rateless coding system with the conventional one which does not utilize LT codes. Simulation results show that the rateless coding system are superior to the conventional system in a large SNR range for slow channel variations and a relative small SNR range for fast channel variations.

The diversity-multiplexing tradeoff, which relates the transmission reliability and efficiency, is an important performance metric in wireless communications. So far only an asymptotic tradeoff result has been obtained for OFDM channels, and such result is only valid for high SNRs. To characterize the outage performance of OFDM systems in realistic SNRs, a finite-SNR framework that analyzes and describes the diversity-multiplexing tradeoff will be proposed in this paper. New upper and lower bounds on outage probabilities will be derived by using the method of integral round a contour, Laurent series, and the properties of Meijer's G-function and Gamma function. The finite-SNR diversity gain, as a function of the multiplexing gain and SNR, will also be computed by Meijer's G-function. We will then show that the finite-SNR diversity-multiplexing tradeoff will converge to the corresponding asymptotic results as SNR tends to infinity. As a result, the finite-SNR diversity-multiplexing tradeoff can be used to estimate the additional SNR required to decrease the outage probability by a specified amount for a given multiplexing gain.

Cognitive radio (CR) is a powerful solution that can significantly improve the utilization of the precious limited radio spectrum. It allows secondary users (SUs) to opportunistically access spectral holes of the licensed spectrum without causing harmful interference to primary users (PUs). However, waiting for idle timeslots may induce very poor quality of service (QoS) for SUs. To alleviate this, an opportunistic relaying protocol exploiting distributed beamforming and token passing is proposed in this paper. We consider a cognitive radio network (CRN), where SUs constitute a two-hop relaying network. Specifically, a distributed beamforming method is applied to enable concurrent transmissions of PUs and SUs, thereby improving the opportunistic spectrum access. Our protocol applies a token passing mechanism in the MAC layer to dynamically balance transmission opportunities between two hops, and hence adapts to the random packet arrival and PUs' presence. We shall formulate a Markov chain to analyze the performance of this protocol. Numerical results show that our proposed protocol can significantly improve QoS of SUs in terms of the packet-loss rate and average delay, compared to conventional relaying protocols that utilize only silent timeslots.

Cognitive radios are efficient techniques to improve the utilization of the spectrum. Spectrum sensing is the key functionality to improve the spectrum efficiency and avoid harmful interference to the licensed users. By exploiting the spatial diversity of the different secondary users, cooperative sensing can achieve better sensing performance compared to the local sensing, thereby, receiving much attention recently. However, in large scale cognitive radio networks, such as Wireless Regional Area Network (WRAN) defined by IEEE 802.22, the secondary users may have quite different sensing SNRs due to the different pass loss and other environment parameters. How to efficiently transmit and fuse the sensing data of cooperative sensing in large scale cognitive radios have not been fully studied yet. This paper presents a sequential sensing data transmission and fusion approach for large scale cognitive radios to minimize the average sensing time by dividing the users into different sets according to their SNR parameters. The analytical and simulation results both show that the proposed approach not only decreases the sensing time but also certifies the accuracy of detection.

Rateless codes can be used for mutual information accumulation in multi-hop wireless networks. However, the impact of spatial reuse and/or node cooperation on performance of the linear multi-hop network employing rateless codes has not been carefully studied yet. In this paper, we present three rateless coded forwarding schemes in linear multi-hop networks, namely, multi-hop forwarding with no spatial reuse, multi-hop forwarding with spatial reuse, and cooperative forwarding with spatial reuse. By analyzing and comparing their performance, we conclude that mutual information accumulation with spatial reuse improves the average throughput but induces a larger latency, while node cooperation, based on rateless codes and spatial reuse, reduces the average delay but suffers a throughput loss.

OFDMA performs a fundamental role in wired/wireless communications. One of the key techniques in OFDMA is the resource allocation, which has been attaching much attention from both academia and industry. In this paper, we describe an innovative combinatorial method to study this problem. An OFDMA system will first be formulated into a random bipartite graph (RBG). To meet various system configurations and requirements, different matching methods will be proposed to perform subcarrier allocation. By studying the properties of RBG matching, we will obtain close-form formulas for outage probabilities so as to evaluate the performance of subcarrier allocation algorithms. It is then demonstrated that by exploiting the frequency diversity and multi-user diversity, the proposed matching method can minimize the outage probability with fairness assurance, and achieve the same diversity-multiplexing tradeoff as point-to-point OFDM systems. The induced subcarrier allocation algorithms also enjoy a sub-linear computation complexity of O(N2/3) for parallel implementations, where N is the number of subcarriers. Besides, the proposed RBG matching method only needs one-bit CSI feedback.

In a frequency-division multiple access satellite communication (SATCOM) system, how to effectively reduce the non-linearity of high-power amplifier to improve the transponder power utility and system capacity, which is the key goal of link supportability analysis, is a challenging and essential step in system design. In this study, the authors creatively model the link supportability analysis problem as a min–max optimisation for a digital channelised SATCOM system, and propose an effective variable neighbourhood search (VNS) algorithm for the established optimisation. By minimising the maximum of carrier powers output from the satellite transponder, the established min–max optimisation model aims at reducing the difference among carrier powers in the satellite transponder as much as possible to avoid carrier power being irregular so that the authors can optimally set the transponder's operating point to improve the transponder power utility, and minimise each terminal's uplink effective isotropic radiated power (EIRP) so that as many links as possible could be supported in the system and thus the system capacity could be enhanced. Practical examples are also presented to verify the proposed approach's superior performance in improving a digital channelised SATCOM system's transponder power utility and the system capacity.

Spectrum sensing is one of the key functionalities in cognitive radios which enables opportunistic spectrum access. In a cognitive radio system, secondary users need to detect the emergence of primary users as soon as possible to avoid harmful interference. In particular, sensing performance can be evaluated by detection delay and sensing overhead. Sequential detection techniques such as quickest detection can achieve minimum detection delay, while MAC layer sensing scheduling of periodic energy detection has demonstrated its high sensing efficiency. These motivate us to propose a joint PHY-MAC spectrum sensing algorithm in this letter, which employs sequential probability ratio test in the PHY layer and a probability-based sensing scheduling mechanism in the MAC layer. This algorithm can minimize detection delay with limited sensing overhead. Simulation results reveal that it has remarkable performance improvement compared with periodic energy detection.

This paper considers the problem of optimal subcarrier allocation in OFDMA systems to achieve the minimum outage probability while guaranteeing fairness. The optimal subcarrier allocation algorithm and the maximum frequency diversity gain are both analyzed through the maximum matching method based on the random bipartite graph theory. Accordingly, a surprising result is found, which shows that the maximum frequency diversity gain in subcarrier-sharing OFDMA systems is the same as that in point-to-point OFDM systems that serve only one user by using N subcarriers. It is then demonstrated that this maximum frequency diversity gain can be achieved by a proposed Random Vertex Rotation based Hopcroft-Karp (RVRHK) algorithm with the time complexity of O(N2.5), where N is the number of subcarriers. Because the theoretical analysis and the RVRHK algorithm are both based on the maximum matching method, the maximum frequency diversity in OFDMA systems is referred to as the max-matching diversity in this paper.

OFDMA technology can significantly improve the transmission reliability and efficiency because of its inherent frequency diversity and frequency multiplexing. In our recent work [B.Bai,W.Chen, Z.Cao and K. B. Letaief (2009) ], we have derived the optimal diversity-multiplexing tradeoff for OFDMA systems under the assumption that each subcarrier occupies the entire coherence bandwidth. However in practical OFDMA systems, such as IEEE 802.16, there are many subcarriers in one coherence bandwidth, i.e., each coherence bandwidth is split into multiple subcarriers which brings the correlation of channel gains among these subcarriers. In this paper, we focus on the diversity-multiplexing tradeoff in this kind of OFDMA systems. First, a correlated random bipartite graph is adopted to formulate this problem. To resolve the user conflicts in subcarrier allocation, the maximum proper /-matching method is introduced to minimize the user outage probability with fairness assurance at given multiplexing gains. Based on this model, the optimal diversity-multiplexing tradeoff curve is obtained. Two extreme points are considered: (1) the full diversity gain is the number of coherence bands, i.e., the same as that in point-to-point OFDM systems; and (2) given a coherence bandwidth, the maximum multiplexing gain is equal to the frequency band equally allocated to each user. The random vertices rotation and extension based Hopcroft-Karp algorithm is then proposed as an optimal subcarrier allocation scheme, which can achieve the optimal tradeoff curve with the time complexity of O(S2.5), where S is the total number of subcarriers.

OFDMA is a potential technology that can flexibly allocate subcarriers while providing diversity gain to multiple users. In our recent work, we showed a surprising result that the maximum frequency diversity gain in OFDMA systems is equal to the number of independent subcarriers, i.e., the same as that in point-to-point OFDM systems despite of the fact that multiple users will share a common set of subcarriers. However, the diversity gain only characterizes the first-order outage performance in the high SNR regime, and the outage performance in the low SNR regime, which is very important in practice, is still an open problem. In this paper, we first formulate the subcarrier allocation problem in OFDMA systems as a random bipartite graph model. Then, a more precise outage probability is derived in the high SNR regime using a high-order analysis of the maximum matching on a random bipartite graph. An approximate outage probability in the low SNR regime is also obtained by studying the complement of a random bipartite graph. It is then demonstrated that the coefficient of the second-order term in the outage probability expression is zero except for the scenario of two users with two or three subcarriers.

Cognitive radio is a powerful solution that can significantly improve the utilization of the precious limited radio spectrum. It allows secondary users (SUs) to opportunistically access spectral holes in the licensed spectrum without causing harmful interference to primary users (PUs). However, the secondary communication opportunity becomes extremely poor when primary systems are heavily loaded. In this paper, a distributed beamforming method is proposed to allow concurrent transmissions of PUs and SUs, thereby improving the opportunistic spectrum access. Specifically, a SU source broadcasts a message to a set of cognitive users, which can serve as a set of relays, when PUs are absent. The relays that correctly decode the message will create a distributed beamformer to forward the message to the SU destination without causing any interference irrespective of whether PUs are silent or not. To achieve this, we use the method of orthogonal projection to obtain the beamforming weight vector. In addition, we derive the distribution of the received signal power at the SU destination, based on which the average outage probability of our proposed scheme is analyzed when PUs' occupation changes fast. Theoretical and numerical results reveal that the spatial diversity order of this scheme equals the number of SU relays minus that of primary receivers. Furthermore, numerical results show that the outage probability of this scheme outperforms other schemes that access the spectrum only when PUs are absent.

Existing spectrum management policies have led to significant over-allocation and under-utilization of the licensed spectrum. To overcome this, cognitive radio is proposed for secondary users to share the licensed spectrum without causing harmful interference to primary users. As such, the transmit power of a secondary user is limited even when it accesses the spectrum hole. Therefore, multihop transmission is a potential method to deliver the data of secondary users over large distance. In such relay systems, the utilization of rateless codes is suitable for the opportunistic spectrum access of cognitive radio. There has been some work in this area. However, the multi-relay cognitive communication with rateless codes has not been carefully investigated. In this paper, we propose a rateless coding based cooperative transmission scheme for cognitive radio networks, where the average end-to-end throughput is analyzed and optimized. We also propose a block search algorithm to find the optimal number of decoding relays with low complexity. Simulation results show that the optimized relay cognitive cooperative transmission can achieve the maximal throughput.

OFDMA technology can significant improve the transmission reliability in multi-user communication systems because of its inherent frequency diversity. In a recent work, we have derived a surprising result which demonstrates that OFDMA systems can achieve a frequency diversity gain which is equal to the total number of independent subcarriers. In this paper, we shall show that the frequency diversity and the frequency multiplexing can be simultaneously achieved in OFDMA systems with a fundamental tradeoff between them. The random bipartite graph theory is used to model and analyze this diversity-multiplexing tradeoff problem. In particular, the maximum proper f-matching is introduced as a subcarrier allocation method which can minimize the user outage probability with fairness assurance given some multiplexing requirements. Similar to the Zheng-Tse tradeoff in MIMO systems, the optimal diversity-multiplexing tradeoff in multi-user OFDMA systems and it will be shown that its curve can be characterized by a piecewise linear function, despite of the user conflicts in the subcarrier allocation.

With the proliferation of wireless multimedia applications, multicast/broadcast has been recognized as an efficient technique to transmit a large volume of data to multiple mobile stations at the same time. In most multicast systems, the transmitter (e.g. base station) adapts its data rate to the furthest located users, so as to guarantee service quality to as many users as possible. Predictably, the more users in a multicast group, the lower data rate the base station can transmit. On the other hand, grouping more users together leads to a more efficient utilization of spectrum bandwidth, as these users are served simultaneously. This bring the interesting problem that presses for solution: how to group users in a cell into multicast groups and how to allocate a fixed amount of bandwidth resource to the groups, to achieve a good balance between throughput and fairness in multicast systems. In this paper, we formulate the united user grouping and bandwidth allocation strategy into a utility-based optimization problem. One method of signomial programming is used to solve the non-convex optimization problem. Numerical results will show that this suboptimal algorithm performs well even compared to the optimal one. Moreover, through theoretical analysis, we prove that the best user grouping and bandwidth allocation scheme of throughput maximization is to allocate the entire bandwidth to the unique group containing the users located within a ring-shaped region with an optimal outer radius r*.

In cognitive radio networks, knowledge of the position of the primary users is very important as it can be used to avoid harmful interference to the primary users, while at the same time be exploited to improve the spectrum utilization. In this paper, a semi range-based localization algorithm is proposed for the secondary users in cognitive radio networks to estimate the positions of the primary users. The basic idea of the proposed algorithm is to take advantage of the estimated detection probabilities, which can be obtained from the binary detection indictors of the secondary users, in order to estimate the distances between themselves and the primary users. The accuracy of the proposed localization algorithm is further improved by introducing an iterative least squares algorithm. The Cramer-Rao lower bound of the mean square error of the proposed localization estimator is also derived. Extensive simulations will then show that the actual mean square error achieved by the proposed localization algorithm is reasonably close to the lower bound, which demonstrates that the proposed method is near optimal.

Due to the broadcasting nature of wireless transmission, concurrently active links can cause mutual interference to each other. This greatly limits the throughput, as well as, results in poor communication reliability especially for wireless systems with multiple links or hops. To overcome this limitation, many interference cancellation techniques, which have mainly focused on the interference among single-hop links, have been designed. In this paper and in contrast to most previous work, we present an efficient method, which we refer to as network interference cancellation or NICE, for effectively mitigating the interference from multi-hop transmissions. This method will make use of the prior knowledge about the interference, which an interfered node can obtain by receiving and processing the signals from the source node of a multi-hop transmission. Two NICE protocols, namely, decode-and-cancel, and amplify-and-cancel are proposed and analyzed. The two proposed protocols will be considered in relay-assisted wireless access networks as well as wireless ad hoc networks without fixed infrastructure to demonstrate the potential of NICE. It will be shown that by using NICE, more links are able to transmit simultaneously in the same frequency band, thereby, highly improving the spatial reuse of spectrum along with the throughput. Numerical results will also show that both of the two NICE protocols can achieve more than 30% throughput gain over conventional interference free scheduling methods.

OFDM can provide frequency diversity gain for point-to-point communications over frequency-selective slow fading channel. Recent works show that OFDM may also form a flexible and efficient multiple access method, which is often referred to OFDMA. However, the user outage probability and the optimal frequency diversity gain in OFDMA systems are not known. In this paper, random bipartite graph is used to model and analyse the multi-user subcarrier allocation problem over frequency-selective slow fading channels. Our aim is to minimize the user outage probability as well as guarantee fairness by dynamic allocating various subcarrier to each user. An optimal subcarrier allocation algorithm, which we shall refer to as the Hungarian method with random vertices rotation, is introduced to achieve these objectives. A simple but effective approximation equation for user outage probability is then derived. It is shown that the optimal frequency diversity gain in OFDMA system is the same as the point-to-point OFDM system. In particular, the frequency diversity gain does not decay as the number of users increases.

With the proliferation of wireless multimedia applications, multicast/broadcast has been recognized as an efficient technique to transmit a large volume of data to multiple mobile stations at the same time. In most multicast systems, the transmitter (e.g., base station) adapts its data rate to the worst channel among all users in the multicast group, so as to guarantee service quality to each user. Predictably, the more users in a multicast group, the lower data rate the base station can transmit. On the other hand, grouping more users together leads to a more efficient utilization of spectrum bandwidth, as these users are served simultaneously. A natural question that arises is how to group users to maximize the throughput of multicast systems, given a fixed amount of bandwidth resource. In this paper, we attempt to answer this important question that has not been addressed before. Through theoretical analysis, we prove that (1) the average throughput increases with the number of users in a multicast group, when the number of subcarriers allocated to a group is proportional to the number of users therein. Moreover, the throughput approaches infinite-bandwidth Gaussian channel capacity when the number of users gets large; (2) the number of users, and hence the number of subcarriers, that is needed for throughput to be arbitrarily close to its asymptotic value increases almost linearly with the transmit SNR. Our analysis is validated through simulations.

Power allocation is an important issue for spectrum sharing of unlicensed bands, in which multiple unlicensed systems may coexist and operate. Recently some works have been reported on game theoretical analysis for multiple systems cooperating in frequency-flat unlicensed bands. However, there has not been much work on the cooperative and competitive strategic behavior of multiple mutually interfering systems in frequency-selective unlicensed bands. In this paper, we construct a game theoretical framework for multiple selfish systems on frequency-selective Interference Channels (IC). This framework enables us to utilize existing protocols designed for frequency-flat ICs in frequency-selective scenarios and can be regarded as an extension of previous results for frequency-flat scenarios.

In Mobile Ad hoc NETworks (MANETs), random access and dynamic routing are two critical techniques for mobile nodes to convey information without centralized scheduling. Conventionally, random access and dynamic routing are implemented at the Medium Access Control (MAC) and the network layer, respectively. However, the current MAC protocol Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) cannot support dynamic routing efficiently. To overcome this limitation, we shall propose a cross-layer protocol which takes dynamic routing into consideration when the mobile nodes contend to access the channel. In the proposed distributed protocol, the routing packets of the network layer are transmitted within the contention period. Since the transmission of routing packets is separated from data transmission in the time-domain, our cross- layer protocol eliminates the collision caused by the transmission of short routing packets. Simulation results will show that our design could significantly improve the system performance at both the MAC and network layers.

In future wireless communication area, a key issue is the resource allocation and scheduling over wireless channel. Various aspects of this issue have been studied. However, few studies are on the QoS guaranteed uplink multiple traffic scheduling in multi-user wireless network. The scheduling problem is addressed in this paper. We consider the TDM-OFDMA uplink multi-access queuing system with four types of traffic. Each type has specific QoS requirements, such as minimum rate, maximum latency and maximum jitter. This QoS guaranteed cross-layer scheduling issue is modeled as a convex optimization problem. We also prove our scheduling method can guarantee the minimum rate, maximum latency and maximum jitter asymptotically, meanwhile it also minimizes the residual integrated workload. According to the solvability of this optimization problem, we define the scheduling algorithm stability region, and design a heuristic algorithm for connection admission control. The numerical results show the substantial performance of the proposed algorithm.

Cognitive radio (CR) is an emerging and powerful solution that can significantly improve the utilization of limited radio spectrum resources by allowing secondary users to borrow unused spectrum from primary licensed networks. In conventional CR protocols, a secondary user (SU) is allowed to transmit only when the primary users (PU) are not active. However, waiting for idle timeslots may induce large packet delay and loss and result in poor quality of service (QoS) for the secondary user. To overcome this, a joint coding and scheduling method for cognitive multiple access is proposed in this paper. In the physical layer, a successive interference decoder is utilized to thoroughly mitigate the SU's interference to PU. A joint channel- aware and queue-aware scheduling protocol is then proposed, at the MAC layer, to minimize the average packet delay of SU given an average transmit power constraint. We shall formulate Markov models to derive the analytical results of delay, packet- loss rate, and power consumption of the proposed scheme. The optimal scheduling parameter and the minimal average delay are also obtained by solving a cross-layer optimization problem.

Dynamic resource allocation is a key technique that can significantly improve the performance of next generation wireless systems under guaranteed QoS to users. Most of the current resource allocation algorithms are, however, limited to unicast traffics. In practice, how to efficiently allocate various resources in multicast wireless systems is not known. In this paper, we shall study dynamic resource allocation for OFDMA-based single-cell multicast systems. Specifically, we shall formulate an optimization problem to maximize the system throughput given a set of available resources (power and sub-carriers). The optimal resource allocation solution is proposed along with a low- complexity algorithm. In two extreme cases, namely, low and high SNR regimes, the low-complexity allocation algorithm is further simplified. Numerical results will show that the system throughput is significantly improved by using our proposed algorithms.

Cognitive Radios allow secondary users to share the spectrum with primary users. The fairness between secondary users in Cognitive Radio networks is an important issue. This paper analyzes the fairness based on the distributed opportunistic spectrum access scheme. A fair multiple access scheme using fast catch-up strategy is proposed. The theoretical result of the first passage time to achieve fairness is given. Simulation results demonstrate that the Fair OSA scheme can achieve fairness much faster when a new secondary user accesses the spectrum. A complex practical scenario is simulated to validate the fairness in more general situations.

A recent development in wireless communication is Cognitive Radio (CR) technology, an innovative radio design approach which allows the realization of intelligent allocation of the scarce radio resources such as spectrum. In this paper, we attempt to exploit past channel information and the flexibility of non-contiguous orthogonal frequency division multiplexing (NC- OFDM) based CRs to maintain end-to-end QoS performance under dynamic spectrum sharing environments. So far, most research works in resource allocation in CRs have mainly concentrated on the spectrum opportunity discovery aspect while the robust QoS performance problem has remained largely unexplored. In this work, we use the concept of portfolio optimization to achieve QoS maintenance in NC-OFDM CR systems. The problem of allocating power to maintain throughput is cast into a channel gain variance minimization and mean- variance maximization frameworks to achieve a given throughput performance under fixed BER and power limitation constraints. Numerical results are presented to demonstrate the QoS maintenance performance in various wireless channel settings.

Node cooperation is an emerging and powerful solution that can overcome the limitation of wireless systems as well as improve the capacity of the next generation wireless networks. By forming a virtual antenna array, node cooperation can achieve high antenna and diversity gains by using several partners to relay the transmitted signals. There has been a lot of work on improving the link performance in cooperative networks by using advanced signal processing or power allocation methods among a single source node and its relays. However, the resource allocation among multiple nodes has not received much attention yet. In this paper, we present a unified cross- layer framework for resource allocation in cooperative networks, which considers the physical and network layers jointly and can be applied for any cooperative transmission scheme. It is found that the fairness and energy constraint cannot be satisfied simultaneously if each node uses a fixed set of relays. To solve this problem, amulti-statecooperationmethodology is proposed, where the energy is allocated among the nodes state-by-state via a geometric and network decomposition approach. Given the energy allocation, the duration of each state is then optimized so as to maximize the nodes utility. Numerical results will compare the performance of cooperative networks with and without resource allocation for cooperative beamforming and selection relaying. It is shown that without resource allocation, cooperation will result in a poor lifetime of the heavily-used nodes. In contrast, the proposed framework will not only guarantee fairness, but will also provide significant throughput and diversity gain over conventional cooperation schemes.

Network coding is an emerging and powerful solution that can significantly improve the throughput and power efficiency of wireless networks by allowing mixing of various traffic flows via algebraic operations. With network coding, however, a packet has to wait to be network-coded with others given the stochastic nature of the packet arrival process of the various flows. This may result in large delay and packet-loss rate. To overcome this limitation, a novel network coding approach, which we shall refer to as opportunistic network coding (ONQ, is presented in this paper. In this proposed approach, whether a packet is transmitted with or without network coding is determined by the buffer's queue state at a given node. We shall derive ONC's performance in terms of delay, packet-loss, and power consumption by formulating a Markov Chain and a Hidden Markov Model for the delay and power analysis. More importantly, we will develop an optimal ONC strategy with minimal average delay and zero packet-loss rate. In particular, we will show that there exists a fundamental tradeoff between average delay and power, which characterizes the performance limit of ONC.

This paper introduces a convergence scheme for digital video/audio broadcasting (BCT) network and broadband wireless access (BWA) network. This convergence scheme supports the architecture based on both PMP topology and mesh topology. It works in the mode of time division with full spectrum multiplexing. Its frame length, BCT time-slot length and BWA time-slot length are adaptive to the arrival traffic and the whole network performance. Then the transmission and the process delay of the token and the performance of the network were analyzed. The main method used is based on M/G/l queue with vacation and time-limited service. The generating function and the mean values for the traffic load distribution in BCT BS and BWA BSs were given. Then it was simulated on the self-similar traffic background and compare with the fixed time-slot allocation scheme. This scheme can reduce the Hurst parameter in some extent.

User cooperation is a powerful solution that can significantly improve the reliability of wireless networks by using several relays to achieve diversity gains. There has been a lot of work on improving the peer-to-peer link quality of a single source-destination pair. However, how to fairly and efficiently allocate resources among multiple nodes has not received much attention yet. In this paper, we propose a novel cooperative diversity method that can achieve fair and efficient resource allocation. We shall show that fairness cannot be achieved by using fixed sets of relays in general. A multi-state cooperation method, where the relay set of each node can be changed, is then proposed to solve this problem. In this proposed approach, the energy is allocated among the nodes via a finite step iterative algorithm. In each step, the relay sets of nodes are changed so that each step will generate a cooperation state, which characterizes the cooperation relationship among the nodes. Based on the energy allocation result, the duration of each state is then optimized so as to minimize the outage probability. We shall show that the proposed method can not only guarantee fairness, but also provide significant diversity gain over conventional cooperation schemes.

Multi-hop wireless networks are expected to play a key role in the next generation wireless systems. In such networks, the presence of multiple links may create severe interference during signal reception and this will greatly limit the network capacity. There has been a lot of work on interference cancellation in single-hop wireless networks. However, how to effectively mitigate interference caused by multi-hop transmission has not received much attention. This paper presents a cross-layer approach for interference cancellation in multi-hop networks. Specifically, two cooperative interference cancellation strategies, which we shall refer to as decode-and-cancel protocol and amplify-and-cancel protocol, are proposed. These schemes take advantage of the presence of a common packet being transmitted through the multiple nodes or hops. It is shown that at a given interfered node, the interference can be estimated and cancelled based upon the received signal of this common packet during the preceding hops. We shall derive the capacity regions of the proposed two protocols and show that they can significantly increase the link capacity.

Triggered update is a common mechanism of the distance vector (DV) algorithm for the acceleration of network convergence and alleviating routing loops. But the traditional triggered update is based on the change of absolute value of state, which is difficult to reflect dynamic characteristics of state fluctuations and may trigger around the trigger boundary or threshold frequently and meaninglessly. This paper proposes a state stability-based triggered update mechanism for DV algorithm (SSB-TU). SSB-TU acquires the stability variety of delay state according to second-moment-based function of statistical parameters and then generates and transfers triggered update. Computer simulation and analysis indicate that, SSB-TU can clearly reflect state fluctuation and guarantee important network performances like network throughput, meanwhile, timely update network state that varies distinctively and efficiently mitigate routing loops.

Multi-hop wireless networks are expected to play an important role in the next-generation wireless systems. One of the central problems in such networks is the network capacity. This paper presents a novel cross layer method for interference cancellation and network coding, which significantly increases the capacity of multi-hop wireless networks. We decompose the multi-hop network into a cell-like sub-network, which we refer to as a wireless switching network. In the proposed approach, multiple nodes, each with its self-information, can communicate via relay nodes. The nodes' self information can then be utilized to cancel the multiuser interference and enable network coding. We shall derive the capacity regions of two cross layer strategies, and show that they are larger than that of the traditional broadcast channel.

In ad-hoc networks, cooperative diversity is especially desired where the use of multiple antennas may be impractical due to the size of nodes. There has been a lot of work on improving the peer-to-peer link quality by using advanced coding or power and rate allocation between a single source node and its relays. However, how to efficiently and fairly allocate resources among multiple users and their relays is still unknown. In this paper, a novel multiuser cooperation protocol is proposed, where multiuser diversity scheme is adopted to schedule different source/destination pairs and each pair computes its required rate based on a power reward. Power reward is adopted by each node to evaluate the power contributed to and by others so as to guarantee fairness. It will be shown that in energy-constrained cooperative ad-hoc networks, fairness can actually bring significant throughput gains. Simulation results will validate our analysis and show that compared to direct transmission and full cooperation protocols, much higher aggregate throughput can be achieved by the proposed Fair Cooperation Protocol thanks to improved fairness.

In multiuser wireless communication systems, dynamic allocation of transmit power is an important means to deal with the time-varying nature both at physical layer and at network layer. Optimal power allocation with perfect channel and buffer state information is studied in this paper. We first build up the cross-layer model by integrating that of physical layer and network layer and then formulate the optimization problem on power allocation. We prove that the optimal solution to power allocation problem can be regarded as an extension of the traditional water-filling (TWF) technique, which is called "water-filling in cellar" (WFIC) policy. The corresponding dynamic programming algorithm is presented. Finally, numerical experiments are employed to illustrate the advantage of our proposed policy.

The system capacity and performance of multicarrier code-division multiple-access (MC-CDMA) communication systems can be significantly enhanced by jointly employing MAP-based multiuser detection (MUD) and channel decoding techniques. In this paper, a group-oriented soft iterative MUD based on the combination of smart antennas and iterative MAP-based MUD is presented. The proposed method is featured as a novel technique for further increasing the system capacity and performance. In this method, all the users are first grouped into several groups according to their impinging direction of arrivals (DOAs). All users with similar DOAs are classified into the same group and then low-complexity MAP-based iterative MUD is employed in each group. Because spatial filtering cannot suppress all the interference between the groups, interference cancellation among the groups is used prior to MUD within each group. It is shown that the proposed group-oriented soft iterative MUD algorithm can significantly reduce the computational complexity compared with the conventional optimal MAP-based MUD schemes. It is also demonstrated that the performance of the proposed algorithm can approach that of a single-user coded MC-CDMA system with an antenna array in additive white Gaussian noise and frequency selective fading channels.

We analyze the maximum throughputs of slotted-ALOHA-based multihop ad hoc networks with and without capture, by considering the degree (number of neighbors) of each node, and, different from prior research, allowing each node to have a different transmission probability. We propose a novel enhanced slotted ALOHA scheme, in which each station adaptively transmits packets according to the degrees of the stations' neighbors. The analytical and simulation results show that the enhanced scheme can improve the network performance greatly.

Dynamic resource allocation combined with adaptive antenna arrays at both the transmitter and receiver can achieve further QoS improvement in conventional OFDM systems. In this paper, we propose two different dynamic resource allocation algorithms with adaptive beamforming for MIMO/OFDM systems and investigate their performance over multipath fading channels under perfect and imperfect CSI. These proposed approaches involve the use of adaptive modulation and adaptive frequency-domain power allocation. By employing this proposed methodology, significant performance improvement can be achieved as compared to the conventional adaptive antenna arrays based on OFDM systems. It is shown, however, that the adaptive modulation based approach is too sensitive to channel estimation errors and that its performance is worse than the adaptive frequency-domain power allocation approach under imperfect CSI.

Narrowband interference (NBI) will degrade the performance in an OFDM system not only on the overlapped subcarriers, but also on the nearby subchannels due to the spectral leakage effect of DFT demodulation. In this paper we proposed a novel NBI suppression method in the case that NBI is caused by a narrowband digital communication system. We estimate the "transmitted data" of NBI signal and reconstruct its waveform, by measuring interference information on certain unmodulated subcarriers. And then subtract estimated disturbance in frequency domain. Simulation results show that this method can achieve an average SINR gain about 6 dB on a multipath fading channel, when the interference has equal power with the desired signal and twice bandwidth of an OFDM bin. With less bandwidth of NBI, more performance gain will be obtained.

Multiuser or joint detection has recently been receiving significant research interest because of its potential for the significant increase in system capacity and performance. Among the conventional multiuser detection schemes such as the minimum mean-squared error and successive interference cancellation-based ones, maximum-likelihood multiuser detection has the best system performance. However, the complexity of maximum-likelihood detection (MLD) increases exponentially in the number of users and constellation size. In this paper, a low-complexity MLD scheme based on the use of a sensitive-bits algorithm is proposed. It is demonstrated that the proposed method can greatly reduce the computational complexity with a minimal penalty in performance compared with the exhaustive optimal MLD scheme.

In recent years, combining multiuser detection (MUD) and channel decoding has received considerable attention. The maximum a posteriori (MAP) criterion-based iterative multiuser detector greatly improves the system performance and can approach the performance of single-user coded systems. However, its complexity increases exponentially with the number of users and can become prohibitive for systems with a medium-to-large number of users. In this paper, a reduced complexity MAP-based iterative MUD based on the use of a soft sensitive bits algorithm is proposed for coded multicarrier code-division multiple-access systems. It is shown that it can greatly reduce the computational complexity with a minimal penalty in performance compared to the conventional optimal scheme.

Orthogonal frequency division multiplexing (OFDM) has been widely regarded as an effective modulation technique for mitigating the effects of intersymbol interference in a frequency selective fading channel and for providing reliable high-data-rate transmission over wireless links. Adaptive antenna arrays at the base and mobile stations can achieve further increases in system's capacity and bandwidth efficiency, as well as in quality-of-service improvement in conventional OFDM systems. The conventional adaptive antenna-arrays-based OFDM systems always use the subcarriers characterized by the largest eigenvalues to transmit the OFDM block symbols. And in contrast to previous work, we propose dynamic spatial subchannel allocation with adaptive beamforming for broadband OFDM wireless transmission systems. The proposed system adaptively selects the eigenvectors associated with the relatively large spatial subchannel eigenvalues to generate the beamforming weights at the mobile and base stations and then dynamically assigns the corresponding best spatial subchannels to transmit the OFDM block symbols. It is shown that the proposed system can achieve better performance than an adaptive antenna-arrays-based OFDM system without dynamic spatial subchannel allocation over multipath fading channels. Simulation results also reveal that the proposed system is far less susceptible to feedback delay in rapid time-varying channels and a little more sensitive to channel estimation errors than conventional adaptive antenna-arrays-based OFDM systems. The performance of the proposed system combined with adaptive modulation is also considered.

Abstract A differential detection scheme for transmit diversity was proposed by Tarokh, which can achieve full diversity order without the requirement to estimate the channel state at the receiver. This paper investigates the potential of using multiple receive antennas for differential space time coded MPSK signals over correlated Nakagami fading channels. We also investigate the effect of the carrier frequency offset (CFO) and channel correlation on its performance and present some results on its maximal tolerable frequency offsets for different MPSK signals. The results have shown that the differential encoding transmit diversity is very robust to the CFO and channel correlation. Copyright © 2004 John Wiley & Sons, Ltd.

In this paper we propose a novel wireless scheduling algorithm for delay-sensitive (DS) and best-effort (BE) traffics. Unlike the majority of the previous wireless scheduling, where the wireless links are modeled as having only two states, our algorithm is applicable to links with multiple states. For DS flows, the algorithm is capable of providing statistical delay violation bounds. Such bounds are derived, analytically, using the idea of the statistical service envelope. For BE flows, we propose a new notion of fairness, called long-term link-quality weighted outcome-fair, which we believe is more suited to wireless networks than pure outcome-fair or effort-fair. The algorithm achieves a balance between bandwidth efficiency requirement and fairness requirement, and guarantees minimal goodput levels for BE flows.

Nonbinary type-II hybrid ARQ (HARQ), which combines shortened Reed-Solomon (RS) code with ARQ, is proposed. Its throughput is obtained by extending Lin and Yu's analysis of binary type-Il HARQ. Analytical results show that nonbinary HARQ outperforms its binary counterpart in throughput over Rayleigh fading channels when the modulation scheme and the FEC subsystem are selected properly.

Adaptive modulation combined with transmit diversity can achieve further increases in system's capacity and bandwidth efficiency, as well as in QoS improvement in conventional OFDM systems. In this paper, we propose a constant rate adaptive modulation with selection transmit diversity for broadband OFDM wireless systems. By combining the adaptive modulation with the adaptive selection diversity according to the characteristics of the channel on each sub-carrier, the transmit diversity obtained by antenna selection is further maximized through adaptive bit assignment and power assignment on each sub-carrier under the constraint of power and overall bit rate. As a result, the proposed system can achieve better performance compared to that of the conventional selection transmit diversity based OFDM systems without adaptive modulation and conventional adaptive modulation based OFDM systems without selection transmit diversity over multipath fading channels.

Cross layer design is a promising approach in mobile ad hoc networks (MANET) to combat the fast time-varying characteristics of wireless links, network topology, and application traffic. In this paper, we employ cross layer design to develop a novel-scheduling scheme with two optimisations aimed at service differentiation. The scheduling scheme is executed at the network layer of every station according to the channel conditions estimated by the MAC layer. The optimizations are based on traffic property sharing and packet timeout period interaction to reduce the packet collisions and improve network performance. We evaluate the proposed scheme under different network loads in terms of packet delivery ratio, average end-to-end delay and delay jitter. The simulation results show that our scheme can provide different service differentiations for time-bounded and best effort traffics. In particular, we can guarantee the delay and delay jitter requirements of time-bounded traffic.

Space-time coded orthogonal frequency division multiplexing (OFDM) is a promising scheme for future wideband multimedia wireless communication systems. The combination of space-time coding (STC) and OFDM modulation promises an enhanced performance in terms of power and spectral efficiency. Such combination benefits from the diversity gain within the multiple-input-multiple-output ST coded system and the matured OFDM modulation for wideband wireless transmission. However, STC transmit diversity impairs the system's interference suppression ability due to the use of multiple transmitters at each mobile. We propose an effective co-channel interference (CCI) cancellation method that employs angle diversity based on null-steering beamforming or minimum variance distortion response beamforming. It is shown that the proposed method can effectively mitigate CCI while preserving the space-time structure, thereby, significantly improving the system's interference suppression ability without significant bit-error rate performance degradation. Furthermore, it is demonstrated that the proposed method can significantly combat the delay spread detrimental effects over multipath fading channels without the use of interleaving.

In previous years, combining multiuser detection (MUD) and channel decoding has received considerable attention. The maximum a posteriori (MAP) criterion based iterative multiuser detector greatly improves the system performance and can approach the performance of single user coded systems even for moderate signal-to-noise ratios. However, its complexity increases exponentially with the number of users, and can become prohibitive for systems with medium to large number of users. A reduced complexity MAP-based iterative MUD based on the use of a soft sensitive bits algorithm is proposed for multi-carrier CDMA systems. It is shown that it can greatly reduce the computational complexity with a minimal penalty in performance compared to the conventional optimal scheme.

Orthogonal frequency division multiplexing (OFDM) has been widely regarded as an effective modulation technique for mitigating the effects of ISI in a frequency selective fading channel and for providing reliable high data rate transmission over wireless links. Adaptive antenna arrays at the base and mobile stations can achieve further increases in system's capacity and bandwidth efficiency, as well as in QoS improvement in conventional OFDM systems. The conventional adaptive antenna arrays based OFDM systems always use the sub-carriers characterized by the first largest eigenvalues to transmit the OFDM block symbols. In this paper and in contrast to previous work, we propose dynamic sub-channel allocation with adaptive beamforming for broadband OFDM wireless transmission systems. The proposed system adaptively selects the eigenvectors associated with the relatively large sub-channel eigenvalues to generate the beamforming weights at the mobile and base stations and then dynamically assigns the corresponding best sub-channels to transmit the OFDM block symbols. It is shown by simulation that, without adding much complexity, the proposed system can achieve a better performance than an adaptive antenna arrays based OFDM system without dynamic sub-channel allocation over multipath fading channels. Simulation results also reveal that the proposed system is not too sensitive to channel estimation errors.

The system capacity and performance of MC-CDMA communication systems can be significantly enhanced by jointly employing MAP-based multiuser detection (MUD) and channel decoding techniques. In this paper, a group oriented soft iterative MUD based on the combination of smart antennas and iterative MAP-based MUD is presented. The proposed method is featured as a novel technique for further increasing the system capacity and performance. It is demonstrated that the performance of the proposed algorithm with low complexity can approach that of a signal user coded MC-CDMA system with an antenna array in AWGN and frequency selective fading channels.

Short BCH codes for multimedia communication are examined in a typical fast fading channel. In adverse fading channel, burst errors degrade the quality of transmission badly. Generally, long BCH codes and large interleaving degree are adopted to improve the performance of system, thus causing inevitable long delay, which sometimes is fatal to multimedia data. We propose to employ short BCH codes (n<32) with medium interleaving depth on static images compressed by discrete-cosine-transformation (DCT), a widely used compression method in multimedia data. The structure of coding meets the rigorous delay request of multimedia communication. Simulation results amply demonstrate the validity of the proposed scheme in fading environment. The aspects of delay and reliability are both satisfied.

Space-time coding is a powerful scheme that combines channel coding, modulation, and multiple transmit antennas to achieve higher data rates and combat fading in wireless systems. In this letter, we propose a multiple-input multiple-output minimum mean-square error spatial-filtering-based adaptive antenna arrays method to suppress cochannel interference (CCI) in space-time coded systems. It is shown that the proposed method can effectively suppress CCI while preserving the space-time structure, thereby significantly improving the system's interference suppression ability without significant bit error rate performance degradation.

The capacity of MC-CDMA communication systems can be significantly enhanced by employing multiuser detection (MUD) techniques. A group oriented MUD based on the combination of smart antennas and multiuser or joint detection is presented. The proposed method is featured as a novel technique for further increasing the system capacity and performance. In this method, all the users are first divided into several groups according to their impinging direction of arrivals (DOA). All users with similar DOAs are classified into the same group and then MUD is employed in each group in parallel. Because spatial filtering cannot suppress all the interference between the groups, interference cancellation among groups is used prior to MUD within the groups. It is shown that the proposed group oriented MUD algorithm can significantly reduce the computational complexity and processing time delay compared with the conventional MUD schemes. Furthermore, it is demonstrated that significant performance improvement can be achieved.

In this paper, we consider the subchannel detection problem in forward links for the multicarrier (MC) DS-CDMA system when some different subchannel allocation policies are used. An optimal subchannel decision algorithm is proposed based on the maximum-likelihood (ML) criterion. The theoretical analysis and simulation results are presented. We also discuss the parameter selection problem for the length of the training sequence in the system model in Pingyi Fan et al. by using the proposed ML detection algorithm. The results show that the subchannel allocation schemes in Pingyi Fan et al. is feasible since only a few symbols overhead are required.

Space division multiple access (SDMA) is a promising solution for the significant increase of system capacity and spectral efficiency in wireless LANs. To make the system more robust against the detrimental effects of frequency selective fading channels, a combined OFDM/SDMA based WLAN has been previously proposed. In particular, it has been shown that MLD (maximum likelihood detection) has the best SNR performance compared with other detection schemes such as LMMSE and SIC (successive interference cancellation) based ones. However, the complexity of MLD increases exponentially in the number of users and constellation size. In this paper, a new multi-stage low complexity MLD scheme using the sensitive bits algorithm (SB-MLD) is proposed. It is shown that it can greatly reduce the computational complexity with a minimal penalty in performance compared with the exhaustive MLD scheme.

Space-time coded OFDM is a promising scheme for future wideband multimedia wireless communication systems. The combination of space-time coding (STC) and OFDM modulation promises an enhanced performance in terms of power and spectral efficiency. However, STC transmit diversity impairs the system's interference suppression ability because each transmitter generates multiple signals that appear independent to the receiver antenna arrays. In this paper, we propose a novel CCI cancellation method employing angle diversity based on beamforming. It is shown that the proposed method can effectively mitigate CCI while preserving the space-time structure, thereby, significantly improving the system's interference suppression ability without significant performance degradation.

The paper presents a low complexity channel estimator based on windowed discrete Fourier transform (DFT) and scalar Wiener filter for orthogonal frequency division multiplexing (OFDM) mobile communications systems. In the method, a generalized Hanning window is applied to the channel frequency response observation vector in the frequency domain to reduce the spectral leakage, and a scalar Wiener filter is applied to the effective channel impulse response in the time domain to suppress the channel noise. Analysis results show that the proposed method's performance is close to the optimal minimum mean square error (MMSE) estimator and is much better than the direct DFT based estimator. Compared with the optimal MMSE estimator, however, the computation load of the proposed method can be significantly reduced because the IDFT/DFT transforms can be implemented with the fast algorithms IFFT/FFT.

A new trellis decoding method of block codes based on the generalized array codes (GACs) structure over a Rayleigh fading channel is presented. Further researches are also carried out to introduce this GAC-based decoding method to an image communication system. Several GACs, code (8, 4, 4) and its shortened code (7, 4, 3), code (16, 5, 8) and its shortened code (15, 5, 7), code (15, 9, 4) and code (30, 19, 4) with the same minimum Hamming distance, are considered in the system. The results show that the minimum Hamming distance is the key factor of the error-correction capability of GAC rather than the coding length in a Rayleigh fading channel. Furthermore, under the soft decision trellis decoding strategy, the quality of the image, whether uncompressed or DCT-compressed, is greatly improved with the help of the GAC.

Indoor wireless communication systems have grown rapidly because of their clear advantages such as mobility, flexibility, and inexpensive network reconfiguration. In order to offer higher data rates approaching those provided by wired LANs, a combined OFDM/SDMA-based approach is an effective solution for increasing the system capacity and spectral efficiency. However, in multi-user environments, the system performance is limited by co-channel interference. Multi-input-multi-output (MIMO) smart antennas with prior knowledge of the channel at the transmitter is another promising technique for providing significant increase in system capacity and performance in wireless communication systems. We investigate the use of smart antennas at both the base and mobile stations, operating jointly, to maximize the SINR of each user before multiuser detection. By doing so, the performance of multi-user detection is significantly improved.

Low-complexity windowed discrete Fourier transform (DFT)-based minimum mean square error (MMSE) channel estimators are proposed and analyzed for both the interpolation and noninterpolation cases for orthogonal frequency-division multiplexing (OFDM) mobile communications systems. In the proposed method, the frequency domain data windowing is used to reduce the aliasing errors for the interpolation case and get better noise filtering performance for the noninterpolation case. The time domain MMSE weighting is also used to suppress the channel noise for both cases. Moreover, the optimal generalized Hanning window shape is searched to minimize the channel estimation mean square error (MSE). Analysis and simulation results show that the proposed method performance is close to the optimal MMSE estimator and is much better than the direct DFT-based estimator for both cases. Compared with the optimal MMSE estimator, however, the computation load of the proposed method can be significantly reduced because the IDFT/DFT transforms can be implemented with the fast algorithms IFFT/FFT.

We present an improved channel estimation algorithm for orthogonal frequency-division multiplexing mobile communication systems using pilot subcarriers. This algorithm is based on a parametric channel model where the channel frequency response is estimated using an L-path channel model. In the algorithm, we employ the ESPRIT (estimation of signal parameters by rotational invariance techniques) method to do the initial multipath time delays acquisition and propose an interpath interference cancellation delay locked loop to track the channel multipath time delays. With the multipath time delays information, a minimum mean square error estimator is derived to estimate the channel frequency response. It is demonstrated that the use of the parametric channel model can effectively reduce the signal subspace dimension of the channel correlation matrix for the sparse multipath fading channels and, consequently, improve the channel estimation performance.

We present a formula to calculate the bit error rate (BER) of maximum-distance-separable (MDS) codes based on the weight distributions of the codes. Because of the exact number of a certain weight of the codes, the probabilities of decoding error and decoding failure can be achieved for an incomplete decoder. The proposed formula is built by summing up all the probabilities of decoding error and decoding failure properly. Two MDS codes, RS (7,5) and RS (63,45) codes, with a 8PSK modulation scheme in the AWGN channel are chosen to verify the formula. Compared with the conventional upper bound formula, our proposed formula is more consistent with the simulated results, no matter short codes or long codes. The formula can be used widely to calculate the accurate BER of MDS codes.

Orthogonal frequency division multiplexing (OFDM) is an effective modulation technique for high-rate and high-speed transmission over frequency selective fading channels. However, OFDM systems can be extremely sensitive and vulnerable to synchronization errors. In this paper, we present a scheme for performing timing recovery that includes symbol synchronization and sampling clock synchronization in OFDM systems. The scheme is based on pilot subcarriers. In the scheme, we use a path time delay estimation method to improve the accuracy of the correlation-based symbol synchronization methods, and use a delay-locked loop (DLL) to do the sampling clock synchronization. It is shown that by using this scheme, the mean square values of the symbol timing estimation error can be decreased by several orders of magnitude compared to the common correlation methods in both the AWGN and multipath fading channels. In addition, the scheme can track the symbol timing drift caused by the sampling clock frequency offsets.

In this paper, we present a delay-locked loop (DLL) technique for performing a combined symbol and sampling clock synchronization in orthogonal frequency division multiplexing (OFDM) systems. In addition, we propose a symbol timing acquisition algorithm for the DLL. It is shown that by using this combined scheme, we can achieve symbol timing recovery and sampling clock adjustment simultaneously. In particular, the symbol timing estimation error variance can be decreased by several orders of magnitude compared with the common correlation methods in both the AWGN and multipath fading channels.