Intelligent Reflective Surface Assisted Integrated Sensing and Wireless Power Transfer

TL;DR

This paper proposes an IRS-assisted integrated sensing and wireless power transfer system, optimizing beamforming and phase shifts to enhance energy harvesting and sensing performance in transportation networks.

Contribution

It introduces a novel joint optimization framework for IRS-assisted ISWPT systems and develops two algorithms to solve the non-convex problem efficiently.

Findings

IRS improves wireless power transfer efficiency.

Proposed algorithms outperform baseline methods.

Simulation confirms system performance benefits.

Abstract

Wireless sensing and wireless energy are enablers to pave the way for smart transportation and a greener future. In this paper, an intelligent reflecting surface (IRS) assisted integrated sensing and wireless power transfer (ISWPT) system is investigated, where the transmitter in transportation infrastructure networks sends signals to sense multiple targets and simultaneously to multiple energy harvesting devices (EHDs) to power them. In light of the performance tradeoff between energy harvesting and sensing, we propose to jointly optimize the system performance via optimizing the beamforming and IRS phase shift. However, the coupling of optimization variables makes the formulated problem non-convex. Thus, an alternative optimization approach is introduced and based on which two algorithms are proposed to solve the problem. Specifically, the first one involves a semi-definite program technique, while the second one features a low-complexity optimization algorithm based on successive convex approximation and majorization minimization. Our simulation results validate the proposed algorithms and demonstrate the advantages of using IRS to assist wireless power transfer in ISWPT systems.