Enhanced beamforming over multiple iterations for downlink broadcast channels

In this paper, we investigate efficient beamforming schemes for downlink broadcast channels of MIMO systems. Optimal solution to this problem is known to be infeasible due to the prohibitive complexity and recent research focuses on suboptimal approaches with reduced complexity. We first present a progressive beamforming method that maximizes the net gain in sum throughput for newly added users and achieves high sum throughput in MU-MIMO channels. Nevertheless, there is severe asymmetry in the performance between data streams: data streams scheduled at an earlier stage are better protected compared to their counterparts configured in later stages. We then show that inter-stream asymmetry can be substantially alleviated by updating beamforming vectors over iterations. An adaptive algorithm is developed to enhance the efficiency of iterative processing and is shown to substantially improve the system performance with manageable complexity.