Statistical CSI-Based Transmission Design for Reconfigurable Intelligent Surface-aided Massive MIMO Systems with Hardware Impairments

TL;DR

This paper proposes a statistical CSI-based transmission design for RIS-assisted massive MIMO systems considering hardware impairments and phase noise, deriving an analytical rate expression and optimizing phase shifts with genetic algorithms.

Contribution

It introduces a novel long-term angle-based phase shift design for RIS in massive MIMO systems accounting for hardware impairments and phase noise, with analytical rate derivation and optimization.

Findings

Hardware impairments significantly impact system performance.

Long-term angle information-based phase shifts improve achievable rates.

Genetic algorithm effectively maximizes sum and minimum data rates.

Abstract

We consider a reconfigurable intelligent surface (RIS)-aided massive multi-user multiple-input multiple-output (MIMO) communication system with transceiver hardware impairments (HWIs) and RIS phase noise. Different from the existing contributions, the phase shifts of the RIS are designed based on the long-term angle informations. Firstly, an approximate analytical expression of the uplink achievable rate is derived. Then, we use genetic algorithm (GA) to maximize the sum rate and the minimum date rate. Finally, we show that it is crucial to take HWIs into account when designing the phase shift of RIS.