Enhancing User Fairness in Two-Layer RSMA: A Movable Antenna Approach
This work addresses the problem of enhancing user fairness in two-layer RSMA systems for wireless communication users, which is an incremental improvement.
This paper tackles the problem of enhancing user fairness in two-layer rate-splitting multiple access (RSMA) systems. By jointly optimizing beamforming, user clustering, common rate allocation, and movable antenna positions, the proposed scheme achieves significant fairness gains over benchmark schemes.
Enhancing user fairness in advanced multi-user systems like two-layer rate-splitting multiple access (RSMA) is a critical yet challenging task. This letter proposes a novel movable antenna (MA) approach to address this challenge. We formulate a max-min fairness problem, maximizing the minimum user rate, a key metric for fairness, through the joint optimization of the beamforming matrices, user clustering, common rate allocation, and the antenna position vector (APV). To solve this non-convex problem, we develop an efficient two-loop iterative algorithm. The outer-loop leverages the dynamic neighborhood pruning particle swarm optimization method to find a high-quality APV, while the inner-loop optimizes the remaining variables for a given APV. Simulation results validate our approach, demonstrating that the proposed scheme yields significant fairness gains over various benchmark schemes.