Robust Design for IRS-Aided Communication Systems with User Location Uncertainty

TL;DR

This paper develops a robust optimization framework for IRS-assisted communication systems that accounts for user location uncertainty, ensuring reliable QoS with minimized transmit power.

Contribution

It introduces a joint beamforming and phase shift design method that handles location errors using SDP, Taylor expansion, and S-Procedure, which is novel in this context.

Findings

Robust algorithm outperforms non-robust methods in QoS reliability.

The proposed method effectively manages user location uncertainty.

Simulation results validate the robustness and efficiency of the approach.

Abstract

In this paper, we propose a robust design framework for IRS-aided communication systems in the presence of user location uncertainty. By jointly designing the transmit beamforming vector at the BS and phase shifts at the IRS, we aim to minimize the transmit power subject to the worse-case quality of service (QoS) constraint, i.e., ensuring the user rate is above a threshold for all possible user location error realizations. With unit-modulus, this problem is not convex. The location uncertainty in the QoS constraint further increases the difficulty of solving this problem. By utilizing techniques of Taylor expansion, S-Procedure and semidefinite relaxation (SDP), we transform this problem into a sequence of semidefinite programming (SDP) sub-problems. Simulation results show that the proposed robust algorithm substantially outperforms the non-robust algorithm proposed in the literature, in terms of probability of reaching the required QoS target.