IRS-Assisted Massive MIMO-NOMA Networks with Polarization Diversity

TL;DR

This paper proposes a dual-polarized IRS-assisted massive MIMO-NOMA system that leverages polarization diversity to enhance performance and mitigate SIC errors, outperforming traditional systems.

Contribution

It introduces a novel polarization domain multiplexing strategy using dual-polarized IRSs to improve massive MIMO-NOMA performance under imperfect SIC conditions.

Findings

Large IRSs improve system performance over conventional methods.

Polarization diversity benefits users even with SIC errors.

Cross-polar transmissions enhance user performance.

Abstract

In this paper, the appealing features of a dual-polarized intelligent reflecting surface (IRS) are exploited to improve the performance of dual-polarized massive multiple-input multiple-output (MIMO) with non-orthogonal multiple access (NOMA) under imperfect successive interference cancellation (SIC). By considering the downlink of a multi-cluster scenario, the IRSs assist the base station (BS) to multiplex subsets of users in the polarization domain. Our novel strategy alleviates the impact of imperfect SIC and enables users to exploit polarization diversity with near-zero inter-subset interference. Our results show that when the IRSs are large enough, the proposed scheme always outperforms conventional massive MIMO-NOMA and MIMO-OMA systems even if SIC error propagation is present. It is also confirmed that dual-polarized IRSs can make cross-polar transmissions beneficial to the users, allowing them to improve their performance through polarization diversity.