Performance Analysis and Optimization for Distributed RIS-Assisted mmWave Massive MIMO With Multi-Antenna Users and Hardware Impairments

Confronted with the challenges of interruptions and blockages caused by dense obstacles in millimeter-wave (mmWave) communication, we propose to employ a flexible distributed reconfigurable intelligent surface (RIS) assisted massive multiple-input multiple-output (MIMO) system to improve performance in areas with poor coverage. In a scenario featuring multi-antenna user equipments (UEs), we consider the practical additive hardware impairments (AHIs) at transceivers and conduct a comprehensive analysis of their impact on the system performance. Leveraging the pronounced beam directivity inherent in mmWave MIMO, we design phase shifts of RISs and analog beamformers of transceivers to achieve beam alignment. In light of this, we explore a linear minimum mean-square error (LMMSE) equivalent channel estimation method. Furthermore, we derive the closed-form expressions for downlink achievable spectral efficiency (SE) in the presence of AHIs, utilizing statistical channel state information (CSI) and maximum ratio transmission (MRT). Based on the derived closed-form expressions, we propose an efficient power allocation strategy relying on an intelligent algorithm known as primal-dual optimization based deep deterministic policy gradient (PDO-DDPG), which can ensure safe exploration of the agent. Numerical results confirm the accuracy of the derived closed-form expressions, unveil the impact of AHIs on the achievable SE, and verify the effectiveness of the PDO-DDPG based power allocation.