In this paper, we investigate a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted downlink multi-user (MU) simultaneous wireless information and power transfer (SWIPT) system to overcome the performance limitations of SWIPT system caused by environmental factors and the deployment constraints of traditional RIS. We adopt a practical non-linear energy harvesting (EH) model and design a resource allocation algorithm for SWIPT systems. By applying the energy splitting (ES) protocol of STAR-RIS, we aim to improve both the transmission rate and EH. Therefore, we formulate a multi-objective optimization problem (MOOP) to simultaneously maximize both the weighted sum rate and EH, by jointly optimizing the base station (BS) beamforming, STAR-RIS coefficient matrices, and power splitting (PS) ratio. To address the non-convexity and variable coupling, an efficient alternating optimization (AO) algorithm integrating fractional programming (FP) and semidefinite relaxation (SDR) is proposed, which decomposes the original problem into three tractable subproblems solved iteratively. Simulation results indicate favorable convergence behavior of the proposed algorithm and achieve substantial performance gains facilitated by the STAR-RIS. The proposed scheme outperforms benchmark schemes in both sum rate and EH, thereby providing theoretical support for the design of future energy-efficient communication networks.
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