Joint relay beamforming and transceiver processing in multiuser relay network
In this thesis, we focus on joint relay beamforming and transceiver processing in multiuser relay network. First of all, we consider the scenario in which multiple source-to-destination (S-D) pairs intend to communicate with the help of multiple distributed amplify-and-forward (AF) relays. A rank-two beamforming Alamouti scheme is proposed at the sources and relays, and we aim to minimize maximal individual relay power subject to pre-defined SINR requirements. The resulting non-convex optimization problem is solved by ordinary semi-definite relaxation (SDR) and separable SDR approaches. Compared to conventional rank-one scheme, proposed rank-two methods provide one more degree of freedom in optimal solution, and have significantly better performance in terms of min-max per-relay power and optimality gap. Secondly, we consider the scenario where multiple users exchange information with each other via a multi-way multi-antenna relaying. Our objective is to jointly design both relay beamforming and receiver linear processing to maximize the minimum signal-to-interference-and-noise ratio (SINR) under a relay power budget. The joint optimization problem is iteratively solved by designing relay beam matrix and receiver processing matrix. For the latter, both maximum-ratio-combining (MRC) receiver and zero-forcing (ZF) receiver are designed. The MRC receiver leads to the optimal iterative design while the ZF receiver has lower computational complexity. We also use successive interference cancellation (SIC) as our decoding strategy to further enhance sum-rate. Simulation results show that the proposed iterative algorithm yields higher achievable sum-rate than the existing partial ZF (PZF) method which uses sum-rate maximization as the design objective.