Spectral Efficiency Maximization for Fluid Antenna Systems-Enabled MIMO-RSMA Networks

Fluid antenna systems (FASs) introduce dynamic reconfigurability by allowing antenna ports to adjust positions and shapes, thus exploiting additional spatial degrees of freedom for greater diversity and multiplexing, while rate-splitting multiple access (RSMA) mitigates interference by partially decoding a common stream. This paper investigates spectral efficiency (SE) maximization in FAS-enabled downlink multiple-input multiple-output (MIMO) networks incorporating RSMA, aiming to overcome the limitations of traditional fixed-position antennas. We propose a novel framework that jointly optimizes the precoding vectors and FAS port activation under constraints on total common SE, individual user SE thresholds, and transmit power limits. The resulting non-convex mixed-integer optimization problem is highly challenging to solve optimally. To address this, we develop a novel iterative algorithm that decomposes the problem into port activation and beamforming subproblems, and solves them efficiently through Lagrangian duality and quadratic transforms. Simulation results demonstrate fast convergence, typically within 8 iterations, with the proposed FAS-RSMA scheme achieving up to 20-30% higher average SE than random antenna systems and fixed-position antennas, owing to aperture/selection diversity and adaptive interference suppression. Performance scales robustly with increasing transmit power budgets, number of ports, FAS surface area, and user density, while maintaining lower complexity than exhaustive search.