Low-Complexity Resource Allocation for Max-Min Fairness in RSMA Systems

We consider the max-min fairness (MMF) rate optimization problem in downlink rate-splitting multiple access (RSMA) wireless networks. Specifically, under a practical low-complexity beamforming design, the MMF problem is reformu-lated as a convex optimization task and solved using a combination of the improved water-filling approach and the accelerate proximal gradient (APG) method. Simulation results indicate that the proposed approach offers comparable performance to existing methods while significantly reducing computation time. The proposed method closely approximates the minimum user rate derived from MMF optimization and achieves a total rate comparable to that of sum-rate maximization.