RSMA-Enabled Aerial RIS-Aided MU-MIMO System for Improved Spectral-Efficient URLLC

This study explores a new resource allocation framework for a multi-user multiple-input and multiple-output (MU-MIMO) downlink system utilizing aerial reconfigurable intelligent surfaces (ARIS) in a rate-splitting multiple access (RSMA) scheme under ultra-reliable low-latency communication (URLLC). The objective is to maximize the overall spectral efficiency of users located in severely blocked dead zones, where there is no direct link between the base station (BS) and the users and, the ARIS acts as a relay to facilitate communication. To achieve this, we formulate a sum-rate maximization problem considering the joint design of active beamforming at the BS, passive beamforming at the ARIS, and determination of the ARIS height. The constraints include given packet size and packet error probability (PEP) requirements. Since the original problem is non-convex, we propose an alternating optimization framework to solve it. The framework involves solving sub-problems of beamforming design and ARIS location alternately. The beamforming design sub-problem is addressed using successive convex approximation, while the ARIS location sub-problem is solved using a particle-swarm optimization (PSO) algorithm. The proposed solution demonstrates fast convergence within a few iterations, as validated through numerical simulations. Additionally, a computational complexity analysis is performed. The results show that the proposed RSMA scheme for the ARIS-aided DL URLLC system surpasses conventional multiple access schemes in terms of rate performance. The findings highlight the potential of utilizing ARIS and RSMA to enhance the spectral efficiency and meet the requirements of URLLC applications.