Weighted sum power maximization for STAR-RIS-aided SWIPT systems with nonlinear energy harvesting

• Published in: Science China. Information sciences Vol. 67; no. 10; p. 202301
• Main Authors: Shi, Weiping, Pan, Cunhua, Shu, Feng, Wu, Yongpeng, Wang, Jiangzhou, Bao, Yongqiang, Tian, Jin
• Format: Journal Article
• Language: English
• Published: Beijing Science China Press 01.10.2024; Springer Nature B.V
• Subjects: Algorithms; Beamforming; Binary stars; Computer Science; Constraints; Decoding; Energy harvesting; Information Systems and Communication Service; Iterative solution; Nonlinear systems; Optimization; Penalty function; Placement; Power transfer; Receivers; Reconfigurable intelligent surfaces; Research Paper; STAR-RIS; SWIPT; alternating optimization; nonlinear energy harvesting; beamforming
• ISSN: 1674-733X; 1869-1919
• DOI: 10.1007/s11432-024-4102-3

The conventional reconfigurable intelligent surface (RIS) is limited to reflecting incident signals, thereby imposing constraints on the placement of the transmitter and receiver, which hinders achieving comprehensive signal coverage across an entire area. This paper investigates a simultaneously transmitting and reflecting (STAR)-RIS-aided simultaneous wireless information and power transfer (SWIPT) system with a nonlinear energy harvesting model under three different RIS transmission protocols: energy splitting (ES), time switching (TS), and mode switching (MS). The objective of this paper is to maximize the weighted sum power (WSP) of all energy harvesting receivers (EHRs) while ensuring fairness in the collected power among them. This is achieved by jointly optimizing the transmit beamforming at the base station (BS) and the transmission and reflection coefficients at the STAR-RIS, subject to rate constraints for information decoding receivers (IDRs), transmit power constraint at the BS, and coefficient constraints of each element at the STAR-RIS corresponding to the three protocols. Solving this optimization problem poses challenges because of the complicated objective function and numerous coupled optimization variables of the ES STAR-RIS. To address this complexity, an efficient alternating optimization (AO) approach is proposed as an iterative solution method that achieves suboptimal results. The AO algorithm is then extended to MS STAR-RIS and TS STAR-RIS. Specifically, for MS STRA-RIS, binary constraints in the STAR-RIS coefficient optimization subproblem are handled using the first-order approximation technique along with the penalty function method. For TS STAR-RIS, apart from optimizing BS transmit beamforming and STAR-RIS coefficients subproblems, the transmission and reflection time allocation of STAR-RIS also needs optimization. Numerical findings demonstrate that compared to conventional RIS-aided systems, utilizing three different protocols in a STAR-RIS-aided system can enhance power collection at EHRs while expanding the receiver placement range. Furthermore, TS STAR-RIS performs best when the IDRs do not require high achieved rates. Otherwise, ES is the best choice.