Beam Selection via Alternating Optimization for Sum Rate Maximization in Multi User Massive MIMO OFDM Systems

Abstract

Hybrid analog–digital beamforming offers a promising approach to reducing hardware complexity in multi-user millimeter-wave (mmWave) massive MIMO-OFDM systems. This paper explores the joint design of analog beam selection and power allocation to maximize the downlink sum-rate under a total transmit power constraint. We propose a DFT codebook-based alternating optimization (AO) algorithm that integrates convex-relaxation initialization, iterative analog beam refinement, and digital block diagonalization. To ensure practical applicability, the framework incorporates realistic modulation and coding schemes. Simulation results based on standardized channel models demonstrate that the heuristic AO beam selection achieves performance close to exhaustive search while significantly reducing complexity.