Transmission Design for XL-RIS-Aided Massive MIMO System with Visibility Regions

TL;DR

This paper introduces a two-timescale transmission scheme for XL-RIS-aided massive MIMO systems that leverages visibility regions to optimize beamforming and phase shifts, enhancing performance and reducing complexity.

Contribution

It proposes a novel two-timescale transmission scheme considering VRs, deriving a closed-form rate expression, and developing an efficient gradient-based algorithm for RIS phase shift optimization.

Findings

The scheme achieves improved minimum user rate.

The approach reduces system complexity.

Numerical results validate the effectiveness of the algorithm.

Abstract

This paper proposes a two-timescale transmission scheme for extremely large-scale (XL)-reconfigurable intelligent surfaces (RIS)-aided massive multi-input multi-output (MIMO) systems considering visibility regions (VRs). The beamforming of base stations (BS) is designed based on rapidly changing instantaneous channel state information (CSI), while the phase shifts of RIS are configured based on slowly changing statistical CSI. Specifically, we first formulate a system model with spatially correlated Rician fading channels and introduce the concept of VRs. Then, we derive a closed-form approximate expression for the achievable rate applicable to any number of BS antennas and RIS elements, and analyze the impact of VRs on system performance and complexity. Next, we solve the problem of maximizing the minimum user rate by optimizing the phase shifts of RIS through an algorithm based on accelerated gradient ascent. Finally, we present numerical results to demonstrate the performance of the gradient algorithm from different aspects and reveal the low system complexity of deploying XL-RIS in massive MIMO systems with the help of VRs.