Joint Power Allocation and Power Splitting for MISO-RSMA Cognitive Radio Systems With SWIPT and Information Decoder Users

• Published in: IEEE systems journal Vol. 15; no. 4; pp. 5289 - 5300
• Main Authors: Camana Acosta, Mario Rodrigo, Moreta, Carla Estefania Garcia, Koo, Insoo
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Approximation; Cognitive radio; Cognitive radio (CR) system; Energy harvesting; Interference; Maximum power; MISO (control systems); MISO communication; Multiaccess communication; Multiple access; NOMA; Optimization; Particle swarm optimization; particle swarm optimization (PSO); Power transfer; rate splitting (RS); Receivers; Relaxation method (mathematics); semidefinite relaxation (SDR); Silicon carbide; simultaneous wireless information and power transfer (SWIPT); Splitting
• ISSN: 1932-8184; 1937-9234
• DOI: 10.1109/JSYST.2020.3032725

In this article, we investigate the rate-splitting multiple access (RSMA) framework in a multiuser multiple-input single-output (MISO) underlay cognitive radio system with power-splitting secondary users and information secondary users by using simultaneous wireless information and power transfer. The RSMA framework is a novel multiple access method based on linearly precoded rate splitting at the secondary base station, and successive interference cancellation at the secondary receivers, which has shown better performance compared with the traditional space-division multiple access (SDMA) method. In particular, the objective is to minimize the transmit power at the secondary base station subject to the constraints of minimum energy harvesting, minimum data rate, and a maximum power level for allowable interference with the primary users. The challenging problem under consideration is nonconvex, and the solution relies on dividing it into outer and inner optimization problems. Then, we propose a particle-swarm-optimization-based algorithm to solve the outer problem, with the inner problem managed by the semidefinite relaxation method. In addition, we present a comparative scheme based on the successive convex approximation method and a scheme based on SDMA. Finally, simulation results confirm the superior performance of the proposed approach in comparison with the other schemes.