Hybrid Beamforming and Data Stream Allocation Algorithms for Power Minimization in Multi-User Massive MIMO-OFDM Systems

Abstract

A hybrid beamforming structure is suggested as one of the solutions to reduce implementation costs and energy consumption in millimeter-wave massive multiple-input, multiple-output (MIMO) systems. In this study, an optimization problem of resource allocation was formulated to minimize the total system transmission power on downlink under a certain quality-of-service (QoS), such as bit/block error rates and data rates for each user, and the solution was proposed therein. Our proposed stream incremental algorithm can dynamically adjust the number of data streams for each user according to the channel state information. Precoding and combining schemes need to be developed to solve the formulated problem and also are proposed in this paper to be paired up with the stream incremental algorithm. Our proposed algorithms consider the practical modulation and coding scheme for transmission in various data stream allocation and beamforming designs. The proposed algorithms provide beamforming solutions for millimeter-wave massive MIMO systems, which achieve comparable performance to that of a fully digital block-diagonalization (BD) algorithm with a lower implementation cost and outperform those of modified existing hybrid beamforming algorithms. Simulation results demonstrate the efficacy of the proposed schemes by allocating the different numbers of data streams for each user according to the channel state information. The simulation results verified that the proposed method can achieve a good trade-off between complexity and performance on comparison with the modified existing schemes and the full digital solutions.