Robust Beamforming for Practical RIS-Aided RSMA Systems with Imperfect SIC under Transceiver Hardware Impairments

TL;DR

This paper proposes a robust beamforming approach for RIS-aided RSMA systems that accounts for practical hardware impairments and imperfect SIC, improving spectral efficiency and robustness over existing methods.

Contribution

It introduces a comprehensive system model incorporating hardware impairments and residual interference, and develops an efficient optimization algorithm for robust beamforming design.

Findings

Significant performance degradation occurs when hardware impairments are ignored.

The proposed scheme outperforms conventional NOMA in spectral efficiency.

Robust design improves system resilience against hardware imperfections.

Abstract

Reconfigurable intelligent surface (RIS)-aided rate-splitting multiple access (RSMA) systems have demonstrated remarkable potential in enhancing spectral efficiency. However, most existing works rely on ideal hardware, which is unrealistic.In practical deployments, RIS elements suffer from amplitude-phase coupling, where transceivers are subject to hardware impairments (HWI), and successive interference cancellation (SIC) in RSMA networks cannot achieve perfect interference elimination for decoded signals.To address these limitations, we investigate a robust beamforming design for RIS-aided RSMA systems under practical hardware imperfections. We first characterize the asymptotic signal-to-noise ratio (SNR) of practical RIS systems when the beamformer is designed based on ideal RIS model, thereby theoretically quantifying the resulting performance degradation. We then derive a closed-form expression for the distortion noise power induced by transceiver HWI, while also accounting for residual interference due to imperfect SIC. Building on these insights, we establish a comprehensive system model that jointly incorporates all hardware-induced impairments and formulate a multiuser sum rate maximization problem. To solve the resulting non-convex optimization problem, we develop an efficient block variable relaxation algorithm. Simulation results verify that the proposed scheme significantly outperforms conventional non-orthogonal multiple access (NOMA) approaches, and achieves superior robustness compared with benchmark schemes neglecting HWI, imperfect SIC, or amplitude-phase coupling.