Green Rate-Splitting Multiple Access for Multicell and Rate Fairness Maximization

This paper investigates the green design of rate-splitting multiple access (RSMA) for multicell, multiantenna downlink communication systems to maximize rate fairness under quality of service (QoS) constraints. An optimization framework is developed to minimize the weighted sum power consumption by jointly optimizing transmit beamformers, power allocation, and common/private rate split while ensuring per-user minimum rate requirements. The algorithm design explicitly considers the rate fairness among users via a newly proposed green fairness index. The nonconvex transceiver design problems are transformed into tractable forms and efficiently solved by applying tools from alternating optimization and successive convex approximation. Extensive simulations demonstrate that the proposed green RSMA optimization framework can effectively balance the throughput among cell-edge and cell-center users, hence combating the near-far effect. Simulation results show that at 20-dB SNR, green RSMA achieves over 20% and 50% sum rate improvement compared with NOMA and OMA, respectively. Moreover, green RSMA maintains high fairness among users, even when the channel conditions are disparate. When the weakest user is located 120 m from the base station, green RSMA exhibits a 21.2% higher fairness index than NOMA, showcasing its ability to ensure equitable service quality across users. The framework also achieves substantial energy efficiency gains, consuming less power while providing higher data rates than baseline schemes. These results demonstrate the effectiveness of green RSMA in enhancing spectral efficiency, user fairness, and energy efficiency in multicell, multiantenna communication systems, making it a promising solution for sustainable and high-performance wireless networks. This paper investigates the green design of rate-splitting multiple access for multi-cell multi-antenna downlink communication systems to max-imize rate fairness under quality of service constraints. An optimization framework is developed to minimize the weighted sum power con-sumption by jointly optimizing transmit beamformers, power allocation, and common/private rate split while ensuring per-user minimum rate requirements. The algorithm design explicitly considers the rate fairness among users via a newly proposed green fairness index.image