Analysis and allocation of radio resources in cooperative wireless networks

Next generation wireless communication systems need to support data rates much greater than in 3G systems. This will require more efficient utilization of the radio resource by using new and techniques such as cooperative wireless networks. This thesis focuses on the analysis and allocation of radio resources in cooperative wireless networks. In the analysis of radio resources, I investigate the diversity-multiplexing-delay (D-M-D) tradeoff analysis of automatic retransmission request (ARQ) cooperative channels. Diversity gain and multiplexing gain are two benefits provided by fading channels. However, in order to achieve more diversity gain, we need to sacrifice some multiplexing gain, and vice versa. Therefore, the maximum diversity gain that can be provided at each multiplexing gain is of course of interest to the designer of wireless systems. The major contribution of this work is that I derive the optimal D-M-D tradeoff curves for ARQ cooperative broadcast channels with arbitrary number of receive nodes and arbitrary maximum number of ARQ rounds. Interestingly, it is shown that the achievable diversity gain is always restricted by two special situations. The results are compared with previous results on the achievable diversity-multiplexing tradeoff curves of cooperative broadcast channels where no ARQ is taken into consideration. It is shown that significant diversity benefit can be provided by ARQ. Moreover, by utilizing the derived results, the impact of the network geometry on the system performance is also analyzed at high signal-to-noise ratio (SNR) region. In my research on the allocation of radio resources, I devise power, sub-carrier, and route allocation methods for cooperative multi-user OFDMA (Orthogonal Frequency Division Multiple Access) systems. It is shown that good allocation of radio resources in cooperative multi-user OFDMA system can significantly enhance the system performance by exploring the cooperative diversity and multi-user diversity in the system. To achieve this objective, I propose novel cooperation strategies and novel centralized resource allocation algorithms in this thesis. The proposed cooperation strategies achieve the capacity upper-bound when there are only two users in the system. When there are more than two users in the system, they can achieve near upper-bound performance in certain network topologies. The proposed resource allocation algorithms are developed via primal-dual decomposition and are capable of solving relay selection, power and subcarrier allocation problems simultaneously. The complexity of the algorithms increases only linearly with the number of subcarriers in the systems. This is a quite an important feature for future wireless OFDMA systems where the number of subcarriers is usually large. A limitation of the above allocation of radio resources is that it assumes full instantaneous channel state information (CSI) of the system, including instantaneous CSI between the source and the relays, are available to the centralized controller (e.g. the basestation). Such an assumption requires significant overhead when the channels vary fast. Therefore I also investigate the scenario where only long term CSI between the source and the relays are available to the centralized controller. The conclusion provides guidelines to the system designers so that they can decide whether the overhead is worth for the performance enhancement. Finally, I investigate the combination of resource allocation and interference cancellation in cooperative wireless networks. Novel cooperative protocol which utilizes self-information to subtract the interference in two-way communication systems is proposed for multi-user multiple-input multiple-output (MIMO) relay systems. An adaptive relay power allocation algorithm is also developed based on the proposed interference cancellation protocol to further increase the system power efficiency. It is shown that the overall protocol achieves more than 30% capacity gain compared to previously multi-user MIMO cooperative protocols in various system scenarios