Adaptive Cross-Entropy-Based Practical Hybrid Precoding for Massive MIMO-RSMA Systems

Abstract

Rate-splitting multiple access (RSMA) is a promising technique for massive MIMO systems, while hybrid precoding provides an effective means to balance transmission performance and energy consumption. However, existing studies mainly focus on fully-connected architectures, while hybrid precoding design for massive MIMO-RSMA systems with energy-efficient partially-connected architecture remains unexplored in the literature. To fill in this research gap, we propose an adaptive cross-entropy (ACE)-based hybrid precoding scheme. The analog precoder is designed using a probabilistic search over discrete phases, iteratively sampling and updating selection probabilities. Then, the weighted minimum mean-squared error (WMMSE) algorithm is employed to jointly optimize the digital precoder and the common rate allocation. Simulation results demonstrate that the proposed scheme maintains competitive MMF performance while achieving superior energy efficiency.