The authors treat the multiuser scheduling problem for practical power-controlled code division multiple access (CDMA) systems under the opportunistic fair scheduling (OFS) framework. OFS is an important technique in wireless networks to achieve fair and efficient resource allocation. Power control is an effective resource management technique in CDMA systems. Given a certain user subset, the optimal power control scheme can be derived. Then the multiuser scheduling problem refers to the optimal user subset selection at each scheduling interval to maximise certain metric subject to some specific physical-layer constraints. The authors propose discrete stochastic approximation algorithms to adaptively select the user subset to maximise the instantaneous total throughput or a general utility. Both uplink and downlink scenarios are considered. They also consider the time-varying channels where the algorithm can track the time-varying optimal user subset. Simulation results to show the performance of the proposed algorithms in terms of the throughput/utility maximisation, the fairness, the fast convergence and the tracking capability in time-varying environments are presented.

We treat the problem of designing low-density parity-check (LDPC) codes to approach the capacity of relay channels. We consider an efficient analysis framework that decouples the factor graph (FG) of aB-block transmission into successive partial FGs, each of which denotes a two-block transmission. We develop design methods to find the optimum code ensemble for the partial FG. In particular, we formulate the relay operations and the destination operations as equivalent virtual MISO and MIMO systems, and employ a binary symmetric channel (BSC) model for the relay node output. For AWGN channels, we further develop a Gaussian approximation for the detector output at the destination node. Jointly treating the relay and the destination, we analyze the performance of the LDPC-coded relay system using the extrinsic mutual information transfer(EXIT) chart technique. Furthermore, differential evolution is employed to search for the optimum code ensemble. Our results show that the optimized codes always outperform the regular LDPC codes with a significant gain; in the AWGN case, when Protocol-II is employed and the relay is close to the source, the optimized code performs within 0.1dB to the capacity bound.

The authors consider the design of LDPC codes for cooperative relay systems in the half-duplex mode. The capacity of halfduplex relay channels has been studied previously but the design of good channel codes for such channels remains a challenging problem. Employing an efficient relay protocol, we transform the half-duplex relay code design problem into a problem of ratecompatible LDPC code design where different code segments experience different SNRs. The density evolution with conventional Gaussian approximation for single user channels, which assumes invariant SNR within one codeword, is not capable of accurately predicting the code performance for this system. Here we develop a density evolution with a modified Gaussian approximation that takes into account the SNR variation in one received codeword as well as the rate-compatibility constraint. We then optimize the code ensemble using a modified differential evolution procedure. Extensive simulations are carried out to demonstrate that the proposed algorithm offers more accurate prediction of code performance in half-duplex relay channels than the conventional methods, and the optimized codes achieve a significant gain over existing codes.

In this study, we consider the design of LDPC codes for cooperative relay systems in half-duplex mode (namely, "cheap" relay) that are of practical interest. We transform the code design problem into the design of rate-compatible LDPC codes where the SNRs in different parts of one codeword are different. Due to the SNR variation, the conventional density evolution (DE) or extrinsic-mutual-information-transfer (EXIT) is not capable of accurately predicting the code performance. We develop a more refined definition of code ensembles and present a modified DE based algorithm related to the new relay code structure. Our results show that the proposed algorithm is more accurate than the conventional DE or EXIT in this case. We further employ the code optimization based on differential evolution. The optimized "cheap" relay code significantly outperforms existing codes.

The problem of multiuser scheduling in multicarrier (MC) systems under practical physical-layer constraints and implementations is considered. Subchannel allocation is an important resource assignment issue in multiuser MC systems. The multiuser scheduler is decoupled into a multiuser selector and a subchannel allocator, which result in a sub-optimum multiuser scheduler with significantly reduced computational complexity. Given an active user subset and a channel set, the multiuser scheduling problem then refers to the optimal subchannel allocation to maximise the instantaneous system throughput subject to certain fairness constraints. Efficient adaptive algorithms are developed for optimal subchannel allocation. The extension of the algorithms for tracking the time-varying optimum, which occurs in non-stationary environments, is also addressed. Simulation results are presented to demonstrate the performance of the proposed algorithms in terms of the throughput maximisation, the fast convergence, the excellent tracking capability in time-varying environments, the achievable throughput of the proposed multiuser scheduler as well as the long-term fairness.

We treat the throughput analyses of parallel ARQ schemes over correlated MIMO channels with adaptive modulation and coding (AMC). To describe the packet transmission over multiple parallel logic channels, we extend the existing burst- error model for single channel to multiple parallel logic channels. Based on such a packet error model, we derive the throughput of different parallel ARQ protocols. Moreover, to describe the temporally correlated physical channel fading, we generalize the existing Markov model for single channel to multiple parallel channels for MIMO systems. Then we develop a method for calculating the packet-level model parameters from the parameters of the physical-layer model and the MIMO transceiver. Using the above hierarchical throughput analysis framework, we investigate the potential throughput gain or throughput loss of parallel ARQ over the conventional serial ARQ in MIMO systems. Our results reveal that as SNR increases, parallel ARQ can achieve higher throughput gain or less throughput loss compared to serial ARQ; parallel SW can achieve throughput gain in most of the MIMO scenarios but increasing the number of antennas does not always bring higher gain; parallel GBN with large number of antennas and independent buffers can achieve throughput gain; parallel SR incurs throughput loss.

We consider the problem of multiuser opportunistic fair scheduling (OFS) in downlink MISO systems employing beamforming. OFS is performed on a per scheduling interval basis to achieve fair bandwidth allocation. Transmit beamforming provides TDMA systems with the capability of supporting multiple concurrent transmissions. Since the optimal beamforming scheme can be calculated for a given subset of users, the scheduling problem then refers to the optimal user subset selection to maximize the system throughput subject to certain constraints. We propose two practical multiuser schedulers, and then present discrete stochastic approximation algorithms to select adaptively a better user subset. We also consider scenarios of time-varying channels where the algorithm can track the time-varying optimum. We present results to show the performance of the proposed algorithms in terms of fast convergence, time-varying tracking capability and fairness.

We consider the problem of opportunistic fair scheduling (OFS) of multiple users in downlink time-division multiple-access (TDMA) systems employing multiple transmit antennas and beamforming. OFS is an important technique in wireless networks to achieve fair bandwidth usage among users, which is performed on a per-frame basis at the media access control layer. Multiple-transmit-antenna beamforming provides TDMA systems with the capability of supporting multiple concurrent transmissions, i.e., multiple spatial channels at the physical layer. Given a particular subset of users and their channel conditions, the optimal beamforming scheme can be calculated. The multiuser opportunistic scheduling problem then refers to the selection of the optimal subset of users for transmission at each time instant to maximize the total throughput of the system subject to a certain fairness constraint on each individual user's throughput. We propose discrete stochastic approximation algorithms to adaptively select a better subset of users. We also consider scenarios of time-varying channels for which the scheduling algorithm can track the time-varying optimal user subset. We present simulation results to demonstrate the performance of the proposed scheduling algorithms in terms of both throughput and fairness, their fast convergence, and the excellent tracking capability in time-varying environments.

We treat utility-based joint power control and rate allocation in a downlink code division multiple access system, where either the matched-filter or the blind multiuser detection technique is employed at the mobile receivers. Rate allocation is performed on a per-frame basis; whereas within the frame, power control is performed at the symbol basis. A hierarchical rate allocation scheme is proposed, which together with the utility-based power control and the opportunistic fair scheduling scheme, maximizes the instantaneous weighted system throughput and the number of feasible users, and at the same time, guarantees the fairness among all users. In order to apply such a resource allocation framework to systems employing blind multiuser detection, we make use of the recent analytical results on the signal-to-interference-plus-noise-ratio performance of the blind multiuser detectors, assuming multiple spreading codes are used to realize multiple data rates. Our results show that under the utility-based joint power and rate allocation framework, the system capacity is significantly enhanced by using blind multiuser detection and the fairness can be well guaranteed.

We treat the multiuser scheduling problem in MC-CDMA systems. To reduce the implementation complexity, we present an efficient structure for the multiuser scheduler. Given the active users and the channels, the subchannel allocator then aims at maximizing the instantaneous system throughput. We develop a stochastic-ruler based algorithm to achieve the subchannel allocation, and prove its global convergence. We also extend the algorithm to track the time-varying optimum in non-stationary channels. We present simulation results to show the performance of the proposed schemes in terms of the throughput maximization with fast convergence, the excellent tracking capability in time-varying channels, and the small throughput loss of the multiuser scheduler.

In this paper, we treat the rate control and fairness scheduling problem for downlink UBPC systems. An hierarchical rate allocation scheme is proposed, which is based on the analytical performance analysis for the physical-layer constraints in the UBPC system. Using such a rate control algorithm together with the opportunistic fairness scheduling scheme, the UBPC system achieves rate allocation more fairly in the sense that the instantaneous system throughput and the number of feasible users can be maximized, and meanwhile the long-term fairness can be well guaranteed. We present the simulation results to demonstrate the performance of the proposed algorithms in terms of the throughput and the fairness.