RIS-Assisted Integrated Sensing, Communication and Energy Harvesting

Abstract

This paper studies a reconfigurable intelligent surface (RIS)- assisted integrated sensing, communication, and energy harvesting system. The sensing beampattern gain is maximized by jointly optimizing the base station beamforming and RIS phase shifts under communication and energy constraints. A semidefinite relaxation (SDR) benchmark and a low-complexity (LC) alternating algorithm are developed. The SDR method provides a performance reference, while the LC design relies on Lagrangian dual updates and coordinate descent for practical implementation. Numerical results further show that the proposed design maintains sensing performance under different communication and harvesting requirements. Simulations show that the LC design achieves near-SDR performance with lower complexity and effectively captures the tradeoff among sensing, communication, and energy harvesting.