Fast Global Optimization For Hybrid Beamforming in Limited Feedback mmWave Systems

Hybrid beamforming provides a cost effective strategy towards practical deployment of massive multiple-input multiple-output (MIMO) systems. Since the hybrid precoder-combiner evaluation requires channel state information, the computation is performed at the receiver and the evaluated precoders are communicated back to the transmitter. This transmission overhead associated with the precoder feedback can be large when the number of transmit antennas is high. In this work, we study the optimization associated with hybrid beamforming in limited feedback systems. We propose an efficient solution for the optimization under a codebook constraint and prove that the proposed solution is globally optimal when the codebook is orthonormal. The proposed approach is also shown to provide superior performance compared to existing approaches in a limited feedback setup. Further, it exhibits a computational complexity far lower than existing alternatives, making it feasible for deployment in real, resource constrained systems.