Active RIS-Aided Massive MIMO Uplink Systems with Low-Resolution ADCs

TL;DR

This paper investigates an active RIS-assisted massive MIMO uplink system with low-resolution ADCs, deriving an approximate sum rate expression, and proposing a genetic algorithm for optimizing RIS phase shifts to improve performance.

Contribution

It introduces a closed-form sum rate approximation and a GA-based optimization method for active RIS in low-resolution ADC massive MIMO systems, demonstrating performance gains.

Findings

Active RIS outperforms passive RIS in system performance.

The derived sum rate expression accurately predicts system behavior.

Optimization of RIS phase shifts enhances achievable rates.

Abstract

This letter considers an active reconfigurable intelligent surface (RIS)-aided multi-user uplink massive multipleinput multiple-output (MIMO) system with low-resolution analog-to-digital converters (ADCs). The letter derives the closedform approximate expression for the sum achievable rate (AR), where the maximum ratio combination (MRC) processing and low-resolution ADCs are applied at the base station. The system performance is analyzed, and a genetic algorithm (GA)-based method is proposed to optimize the RIS's phase shifts for enhancing the system performance. Numerical results verify the accuracy of the derivations, and demonstrate that the active RIS has an evident performance gain over the passive RIS.