Efficient Optimization Algorithms for Multi-User Beamforming With Superposition Coding

Channel asymmetry and channel correlation are frequently encountered in wireless communication systems. Orthogonal transmission schemes are usually inefficient in dealing with these problems. In this paper, in order to boost the throughput performance for multiple-input multiple-output broadcast communications in the presence of channel asymmetry and/or channel correlation, we study optimization algorithms for multi-user superposition coding beamforming (SCBF). Starting with solving the minimum power optimization problem for the two-user case, we derive the optimal solution structure of the problem and two types of dedicated algorithms that could efficiently find the optimal solutions with all parameter setups. Extensions are then made to the same problem with the signals of more than two users multiplexed in the power domain as well as to the rate region computation problem. Finally, to adapt our algorithms to more general cases, novel hybrid precoding schemes are proposed, where certain user grouping strategy is used to combine zero-forcing beamforming and SCBF. Numerical simulations are provided to show that with our algorithms, a considerable performance gain is achieved by SCBF compared to the other orthogonal transmission methods.