User Selection and Rank Adaptation for Multi-User Massive MIMO with Hybrid Beamforming

Abstract

The fifth-generation (5G) radio access network will introduce the use of higher frequency bands with wider bandwidth and Massive MIMO technology for realizing super high bit rate and higher system capacity of more than 10 Gbps. In Massive MIMO using higher frequency bands, from the point of view of realization, as a novel method for hybrid beamforming (BF) that combines analog BF with digital precoding, joint processing of fixed analog BF and channel state information (CSI)-based precoding (FBCP) has been proposed. On the other hand, the user selection and rank adaptation algorithm are essential techniques for multi-user MIMO because the transmission performance of multi-user MIMO suffers from inter-user interference. However, in multi-user Massive MIMO, the computational complexity for user selection becomes large because MIMO channel matrix is massive. In this paper, we propose a 2-step user selection algorithm for high SHF wideband multi-user Massive MIMO using FBCP. It is shown by computer simulation that the proposed 2-step user selection algorithm can reduce the computational complexity by about 55 % while achieving almost the same throughput performance compared to conventional user selection.