Low-Complexity User Matching and Stream-Based Power Allocation for Multicarrier RSMA Systems

The growing demand for robust services that address diverse user requirements in modern mobile communication systems has intensified the need for efficient resource allocation strategies. In this context, rate-splitting multiple access has emerged as a promising solution due to its flexibility in interference management. This work investigates a multi-user multi-carrier rate-splitting multiple access system with a multiple-input single-output configuration, addressing the weighted sum rate maximization problem. To solve this complex problem, we propose a practical two-stage framework comprising: (1) a novel low-complexity heuristic for user matching, and (2) an optimized stream-based power allocation algorithm that jointly considers all streams. Our approach exhibits significantly lower computational complexity compared to optimization-based benchmarks. In terms of performance, the proposed approach achieves substantial gains of 54.7% and 22.7% over the state-of-the-art benchmark in low- and mid-signal-to-noise ratio scenarios, respectively, considering a system with 8 users and 28 subcarriers. Even in scenarios with a higher number of users, specifically 26 users and 6 subcarriers, the algorithm achieves a gain of 25.1% under low-signal-to-noise ratio conditions. Furthermore, simulations demonstrate that the proposed user matching heuristic achieves a near-optimal performance, closely matching the results of a theoretical exhaustive search in the low-signal-to-noise ratio regime. By effectively balancing performance and computational efficiency, the proposed approach is well suited for modern mobile networks, where practical and scalable resource allocation strategies are essential.