A novel hybrid digital-analog beamforming algorithm with uplink training for TDD systems

Abstract

In contrast to conventional multiple-input-multiple-output (MIMO) systems, precoding in millimeter wave (mmWave) massive MIMO is envisioned to achieve considerable capacity improvement, but at the cost of highly hardware complexity. As a cost-effective alternative, hybrid digital-analog beamforming has drawn considerable attention. In most conventional theoretical researches, ignoring practical implementation, perfect channel state information (CSI) is always assumed. However, whether FDD or TDD, in hybrid beamforming architecture, it is extremely challenging for base station (BS) to obtain perfect CSI. In this paper, based on the channel reciprocity in TDD systems, we propose a novel hybrid digital-analog beamforming algorithm with uplink training to maximize the capacity performance. Owing to uplink training, the requirement of CSI at eNodeB to conduct hybrid beamforming is graciously avoided. With practical RF hardware and unit modulus constraints, the proposed scheme provides useful low-complexity solutions in practical hybrid beam-forming system designs. Simulation results validate the efficiency of the proposed scheme compared with some existing hybrid beamforming schemes.)