Cooperative diversity techniques for future wireless communications systems.

Abstract

Multiple-input multiple-output (MIMO) systems have been extensively studied in the past decade. The attractiveness of MIMO systems is due to the fact that they drastically reduce the deleterious e ects of multipath fading leading to high system capacity and low error rates. In situations where wireless devices are restrained by their size and hardware complexity, such as mobile phones, transmit diversity is not achievable. A new paradigm called cooperative communication is a viable solution. In a cooperative scenario, a single-antenna device is assisted by another single-antenna device to relay its message to the destination or base station. This creates a virtual multiple-input multiple-output (MIMO) system. There exist two cooperative strategies: amplify-and-forward (AF) and decode-and-forward (DF). In the former, the relay ampli es the noisy signal received from the source before forwarding it to the destination. No form of demodulation is required. In the latter, the relay rst decodes the source signal before transmitting an estimate to the destination. In this work, focus is on the DF method. A drawback of an uncoded DF cooperative strategy is error propagation at the relay. To avoid error propagation in DF, various relay selection schemes can be used. Coded cooperation can also be used to avoid error propagation at the relay. Various error correcting codes such as convolutional codes or turbo codes can be used in a cooperative scenario. The rst part of this work studies a variation of the turbo codes in cooperative diversity, that further reduces error propagation at the relay, hence lowering the end-to-end error rate. The union bounds on the bit-error rate (BER) of the proposed scheme are derived using the pairwise error probability via the transfer bounds and limit-before-average techniques. In addition, the outage analysis of the proposed scheme is presented. Simulation results of the bit error and outage probabilities are presented to corroborate the analytical work. In the case of outage probability, the computer simulation results are in good agreement with the the analytical framework presented in this chapter. Recently, most studies have focused on cross-layer design of cooperative diversity at the physical layer and truncated automatic-repeat request (ARQ) at the data-link layer using the system throughput as the performance metric. Various throughput optimization strategies have been investigated. In this work, a cross-relay selection approach that maximizes the system throughput is presented. The cooperative network is comprised of a set of relays and the reliable relay(s) that maximize the throughput at the data-link layer are selected to assist the source. It can be shown through simulation that this novel scheme outperforms from a throughput point of view, a system throughput where the all the reliable relays always participate in forwarding the source packet. A power optimization of the best relay uncoded DF cooperative diversity is investigated. This optimization aims at maximizing the system throughput. Because of the non-concavity and non-convexity of the throughput expression, it is intractable to derive a closed-form expression of the optimal power through the system throughput. However, this can be done via the symbol-error rate (SER) optimization, since it is shown that minimizing the SER of the cooperative system is equivalent to maximizing the system throughput. The SER of the retransmission scheme at high signal-to-noise ratio (SNR) was obtained and it was noted that the derived SER is in perfect agreement with the simulated SER at high SNR. Moreover, the optimal power allocation obtained under a general optimization problem, yields a throughput performance that is superior to non-optimized power values from moderate to high SNRs. The last part of the work considers the throughput maximization of the multi-relay adaptive DF over independent and non-identically distributed (i.n.i.d.) Rayleigh fading channels, that integrates ARQ at the link layer. The aim of this chapter is to maximize the system throughput via power optimization and it is shown that this can be done by minimizing the SER of the retransmission. Firstly, the closed-form expressions for the exact SER of the multi-relay adaptive DF are derived as well as their corresponding asymptotic bounds. Results showed that the optimal power distribution yields maximum throughput. Furthermore, the power allocated at a relay is greatly dependent of its location relative to the source and destination.