Analysis and Optimization of RIS-Assisted Cell-Free Massive MIMO NOMA Systems

TL;DR

This paper investigates RIS-assisted cell-free massive MIMO NOMA systems, addressing practical challenges like imperfect CSI and interference cancellation, and proposes novel optimization algorithms to enhance spectral efficiency.

Contribution

It introduces a joint optimization framework with a new successive-QT algorithm and particle swarm optimization for RIS phase shifts, considering realistic system imperfections.

Findings

RIS-assisted links are more beneficial at low transmit power levels.

NOMA outperforms orthogonal multiple access in spectral efficiency.

The proposed optimization significantly improves system sum spectral efficiency.

Abstract

We consider a reconfigurable intelligent surface (RIS) assisted cell-free massive multiple-input multiple-output non-orthogonal multiple access (NOMA) system, where each access point (AP) serves all the users with the aid of the RIS. We practically model the system by considering imperfect instantaneous channel state information (CSI) and employing imperfect successive interference cancellation at the users end. We first obtain the channel estimates using linear minimum mean square error approach considering the spatial correlation at the RIS and then derive a closed-form downlink spectral efficiency (SE) expression using the statistical CSI. We next formulate a joint optimization problem to maximize the sum SE of the system. We first introduce a novel successive Quadratic Transform (successive-QT) algorithm to optimize the transmit power coefficients using the concept of block optimization along with quadratic transform and then use the particle swarm optimization technique to design the RIS phase shifts. Note that most of the existing works on RIS-aided cell-free systems are specific instances of the general scenario studied in this work. We numerically show that i) the RIS-assisted link is more advantageous at lower transmit power regions where the direct link between AP and user is weak, ii) NOMA outperforms orthogonal multiple access schemes in terms of SE, and iii) the proposed joint optimization framework significantly improves the sum SE of the system.