Weighted Sum-Rate Optimization for Multiuser MIMO Systems

This paper focuses on transceiver design for sum-rate optimization in multiuser MIMO systems with linear processing. Two design criteria are considered: one is to maximize the weighted sum-rate under a total power constraint and the other one is to minimize the total transmit power with a sum-rate requirement. We propose iterative algorithms, which perform optimization in an alternating manner in both virtual uplink and downlink channels. Each iteration contains the optimization of the uplink power, uplink receive filter and downlink receive filter. The power optimization to maximize the sum-rate is carried out by minimizing the product of MSEs, which can be formulated as a geometric programming (GP) problem. The proposed algorithms are proved to be convergent and outperform the existing schemes. Additionally, we show that this alternating optimization approach can be extended to the case with successive interference cancellation (SIC) in the uplink and interference pre-compensation (IPC) in the downlink as well. Simulation results show that the global optimum of sum-rate is achieved for all tested scenarios.