Rate-Splitting Multiple Access for Green Communications: A Survey and Robust Beamforming Design
Zhou, Xiaohua; Fang, Tianyu; Mao, Yijie (2025-01-17)
IEEE
17.01.2025
X. Zhou, T. Fang and Y. Mao, "Rate-Splitting Multiple Access for Green Communications: A Survey and Robust Beamforming Design," in IEEE Internet of Things Journal, vol. 12, no. 10, pp. 14469-14483, 15 May15, 2025, doi: 10.1109/JIOT.2025.3526250
https://rightsstatements.org/vocab/InC/1.0/
© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
https://rightsstatements.org/vocab/InC/1.0/
© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
https://rightsstatements.org/vocab/InC/1.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202504142574
https://urn.fi/URN:NBN:fi:oulu-202504142574
Tiivistelmä
Abstract
Rate-splitting multiple access (RSMA) is gaining increasing recognition as a pivotal technology for advancing green communication networks, primarily due to its proficiency in boosting energy efficiency (EE) and lowering power consumption at the transmitter. In this paper, we commence by offering a concise overview of the latest advancements in RSMA for green communications. Motivated by the limitations identified in existing studies, we then focus on robust beamforming design of RSMA to optimize the ergodic EE with imperfect channel state information at the transmitter (CSIT). We first introduce an enhanced successive convex approximation (ESCA) algorithm, which expands upon the traditional successive convex approximation (SCA) approach for maximizing EE with perfect CSIT and adapts it to the imperfect CSIT scenario. To further reduce the computational complexity, we develop a novel and efficient beamforming optimization algorithm to tackle the ergodic EE problem. A key feature of our proposed approach is the use of the semi-closed-form optimal beamforming structure identified for the ergodic EE problem. Subsequently, we propose a fixed-point iteration (FPI) based algorithm to determine the optimal Lagrange dual variables within the optimal beamforming structure. Numerical results show that both proposed algorithms achieve near-optimal solutions and the efficient semi-closed-form optimization algorithm remarkably reduces the computational complexity. Moreover, this study is the first to present an extensive numerical comparison of the ergodic EE between RSMA and other baseline multiple access techniques under imperfect CSIT. These results further highlight the superior EE gains offered by RSMA, reinforcing its potential as a key enabler for green communication networks.
Rate-splitting multiple access (RSMA) is gaining increasing recognition as a pivotal technology for advancing green communication networks, primarily due to its proficiency in boosting energy efficiency (EE) and lowering power consumption at the transmitter. In this paper, we commence by offering a concise overview of the latest advancements in RSMA for green communications. Motivated by the limitations identified in existing studies, we then focus on robust beamforming design of RSMA to optimize the ergodic EE with imperfect channel state information at the transmitter (CSIT). We first introduce an enhanced successive convex approximation (ESCA) algorithm, which expands upon the traditional successive convex approximation (SCA) approach for maximizing EE with perfect CSIT and adapts it to the imperfect CSIT scenario. To further reduce the computational complexity, we develop a novel and efficient beamforming optimization algorithm to tackle the ergodic EE problem. A key feature of our proposed approach is the use of the semi-closed-form optimal beamforming structure identified for the ergodic EE problem. Subsequently, we propose a fixed-point iteration (FPI) based algorithm to determine the optimal Lagrange dual variables within the optimal beamforming structure. Numerical results show that both proposed algorithms achieve near-optimal solutions and the efficient semi-closed-form optimization algorithm remarkably reduces the computational complexity. Moreover, this study is the first to present an extensive numerical comparison of the ergodic EE between RSMA and other baseline multiple access techniques under imperfect CSIT. These results further highlight the superior EE gains offered by RSMA, reinforcing its potential as a key enabler for green communication networks.
Kokoelmat
- Avoin saatavuus [38821]