Energy-Efficiency Optimization of RIS-Enhanced SWIPT Systems Under HPA Nonlinearity

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Abstract
Reconfigurable intelligent surfaces (RISs) have emerged as a crucial technology for making sustainable and green communication in future sixth-generation (6G) networks. By adaptively adjusting the wireless environment, the RIS facilitates flexible control over signal propagation. When an RIS is integrated into a simultaneous wireless information and power transfer (SWIPT) system, it can improve energy-efficiency (EE) and link reliability. This enables low-power Internet of Things (IoT) devices to achieve continuous energy acquisition while maintaining reliable data access. This capability aligns well with the increasing demands of future 6G networks for enhancing EE and achieving ubiquitous connectivity. Motivated by this, we investigate an RIS-assisted multiuser SWIPT system that accounts for the nonlinear characteristics of the high-power amplifier (HPA) at the transmitting end and the nonlinearity of the energy harvesting (EH) circuits at the receivers. These hardware imperfections pose major challenges for system modeling and optimization, particularly under stringent power limitations and quality-of-service (QoS) requirements, where improving overall EE is a key objective. Therefore, we proposed a joint optimization framework that simultaneously designs the access point (AP) beamforming, the RIS reflection coefficients, and the power splitting (PS) ratios at the receivers. The resulting problem is nonconvex, with strong coupling among these variables. To tackle this issue, we propose an efficient alternating optimization (AO) framework. The fractional EE objective is handled using the Dinkelbach method, while each subproblem is iteratively convexified via successive convex approximation (SCA) and semi-definite relaxation (SDR) algorithms. Simulation results reveal that the proposed AO approach achieves substantial EE gains and confirm that integrating RIS conspicuous boosts the overall system EE performance.
Funding Information
  • National Key Research and Development Program of China (2024YFE0107900)
  • Special Project for Research and Development in Key areas of Guangdong Province (2025B0101200001)
  • National Natural ScienceFoundation of China (U25B2006)
  • National Natural ScienceFoundation of China (62571193)
  • National Natural Science Foundation of China (2024A1515010235)
  • National Natural Science Foundation of China (2024A04J5146)

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