Robust IRS-aided Secrecy Transmission with Location Optimization

TL;DR

This paper introduces a robust secrecy transmission scheme for IRS-assisted systems that optimizes IRS location, beamforming, and phase shifts to enhance security under imperfect CSI, considering known or suspicious Eve locations.

Contribution

It presents a novel joint optimization framework for IRS location, beamforming, and phase shifts, addressing imperfect CSI and Eve location uncertainty.

Findings

Optimizing IRS location significantly improves secrecy rate.

The proposed two-stage framework effectively handles CSI uncertainties.

Simulation confirms the benefit of IRS location optimization for security.

Abstract

In this paper, we propose a robust secrecy transmission scheme for intelligent reflecting surface (IRS) aided communication systems. Different from all the existing works where IRS has already been deployed at a fixed location, we take the location of IRS as a variable to maximize the secrecy rate (SR) under the outage probability constraint by jointly optimizing the location of IRS, transmit beamformer and IRS phase shifts with imperfect channel state information (CSI) of Eve, where we consider two cases: a) the location of Eve is known; b) only a suspicious area of Eve is available. We show a critical observation that CSI models are different before and after IRS deployment, thus the optimization problem could be decomposed and solved via a two-stage framework. For case a), in the first stage, universal upper bounds of outage probabilities only related to the location of IRS are derived which can be optimized via successive convex approximation (SCA) method. In the second stage, we develop an alternative optimization (AO) algorithm to optimize beamformer and phase shifts iteratively. For case b), we propose a Max-Min SR scheme based on two-stage framework, where the location of IRS is optimized based on the worst location of Eve. Simulation results indicate the importance of the location of IRS optimization.