Efficient Robust Beamforming for Downlink Transmission in Massive MIMO Systems

Abstract

Massive multiple-input multiple-output (MIMO) is an emerging technology, which enables future broadband wireless connections. In this paper we investigate the optimization problem of signal-to- interference-plus-noise ratio (SINR) balancing for users in a typical massive MIMO network. We present a fast converging robust beamforming solution for the case of imperfect channel state information at the transmitter. The proposed method applies the Smith form reformulation to transform the original non-convex optimization problem into a standard second-order cone program. The matrix stuffing technique and the alternative direction method of multipliers are then used to provide an efficient solution to the problem. Simulation results show that the proposed solution gives SINR performance with lower accuracy averaging 97%, while it converges to a solution more than twice faster than the optimal solution, which uses CVX and the SeDuMi solver.