Resource allocation for UAV-RIS-assisted RSMA system with hardware impairments

Abstract

The convergence of intelligent reflecting surfaces (IRS), unmanned aerial vehicle (UAV) communication systems, and rate-splitting multiple access (RSMA) heralds a transformative advancement in wireless communication technology. In this paper, we integrate these three pivotal technologies to maximize fairness in downlink hardware-impaired networks. Specifically, we deploy a UAV-mounted IRS to serve single-antenna users from a multiple-antenna base station (BS) with RSMA protocol. This novel approach introduces significant complexity due to the strong coupling of the optimization variables and non-convex nature of the problem. Our study seeks to optimize IRS phase shifts, IRS location, precoding, transmit power, and common rate allocation using a block coordinate decomposition approach. This methodology strives to achieve an equitable distribution of resources among users while accounting for hardware impairments and leveraging the benefits of IRS and RSMA technologies. The coupling of variables makes the optimization problem highly non-convex, significantly increasing its complexity and making the quest for an optimal solution formidable. To address this challenge, we employ successive convex approximation (SCA) and penalty dual decomposition (PDD) methods to handle the non-convex problem and decompose the coupled optimization variables. These approaches facilitate effective exploration of the optimization space while considering the intricate coupling of variables. We propose efficient algorithms for each subproblem. Simulation results demonstrate that RSMA markedly enhances performance in highly impaired networks, leading to improved network performance, better user experience, robust, and efficient resource utilization.