Secrecy Rate Maximization for Intelligent Reflecting Surface Aided SWIPT Systems

TL;DR

This paper addresses the enhancement of wireless security in IRS-aided SWIPT systems by jointly optimizing beamforming and artificial noise to maximize secrecy rate, demonstrating significant improvements through simulation.

Contribution

It introduces a joint optimization framework for secrecy rate maximization in IRS-aided SWIPT systems using an alternating optimization approach.

Findings

Proposed scheme outperforms baseline methods in secrecy rate.

Effective joint design of beamforming and artificial noise.

Simulation results validate the scheme's superiority.

Abstract

Simultaneous wireless information and power transfer (SWIPT) and intelligent reflecting surface (IRS) are two promising techniques for providing enhanced wireless communication capability and sustainable energy supply to energy-constrained wireless devices. Moreover, the combination of the IRS and the SWIPT can create the "one plus one greater than two" effect. However, due to the broadcast nature of wireless media, the IRS-aided SWIPT systems are vulnerable to eavesdropping. In this paper, we study the security issue of the IRS-aided SWIPT systems. The objective is to maximize the secrecy rate by jointly designing the transmit beamforming and artificial noise (AN) covariance matrix at a base station (BS) and reflective beamforming at an IRS, under transmit power constraint at the BS and energy harvesting (EH) constraints at multiple energy receivers. To tackle the formulated non-convex problem, we first employ an alternating optimization (AO) algorithm to decouple the coupling variables. Then, reflective beamforming, transmit beamforming and AN covariance matrix can be optimized by using a penalty-based algorithm and semidefinite relaxation (SDR) method, respectively. Simulation results demonstrate the effectiveness of the proposed scheme over baseline schemes.