Joint Association, Beamforming, and Resource Allocation for Multi-IRS Enabled MU-MISO Systems With RSMA

TL;DR

This paper investigates joint optimization of association, beamforming, and resource allocation in multi-IRS MU-MISO systems utilizing RSMA, proposing two scheduling schemes and demonstrating their effectiveness through advanced optimization techniques.

Contribution

It introduces two IRS-aided scheduling schemes for RSMA systems and develops an optimization framework to maximize energy efficiency, showing improved performance over baseline methods.

Findings

EIA scheme outperforms OIA in energy efficiency across scenarios.

Proposed algorithms surpass baseline algorithms in effectiveness.

Optimization techniques effectively enhance system performance.

Abstract

Intelligent reflecting surface (IRS) and rate-splitting multiple access (RSMA) technologies are at the forefront of enhancing spectrum and energy efficiency in the next generation multi-antenna communication systems. This paper explores a RSMA system with multiple IRSs, and proposes two purpose-driven scheduling schemes, i.e., the exhaustive IRS-aided (EIA) and opportunistic IRS-aided (OIA) schemes. The aim is to optimize the system weighted energy efficiency (EE) under the above two schemes, respectively. Specifically, the Dinkelbach, branch and bound, successive convex approximation, and the semidefinite relaxation methods are exploited within the alternating optimization framework to obtain effective solutions to the considered problems. The numerical findings indicate that the EIA scheme exhibits better performance compared to the OIA scheme in diverse scenarios when considering the weighted EE, and the proposed algorithm demonstrates superior performance in comparison to the baseline algorithms.