Robust Beamforming for IRS Aided MIMO Full Duplex Systems

TL;DR

This paper proposes a robust beamforming method for IRS-assisted full-duplex MIMO systems that accounts for imperfect channel information, maximizing ergodic weighted sum rate and outperforming naive and half-duplex systems.

Contribution

It introduces a statistically robust beamforming approach for IRS-assisted FD systems with imperfect CSI, optimizing ergodic WSR via expected WMMSE.

Findings

Significant performance gains over naive beamforming.

Outperforms robust half-duplex systems.

Effective convergence to a local optimum.

Abstract

In this paper, a novel robust beamforming for an intelligent reflecting surface (IRS) assisted FD system is presented. Since perfect channel state information (CSI) is often challenging to acquire in practice, we consider the case of imperfect CSI and adopt a statistically robust beamforming approach to maximize the ergodic weighted sum rate (WSR). We also analyze the achievable WSR of an IRS-assisted FD with imperfect CSI, for which the lower and the upper bounds are derived. The ergodic WSR maximization problem is tackled based on the expected Weighted Minimum Mean Squared Error (WMMSE), which is guaranteed to converge to a local optimum. The effectiveness of the proposed design is investigated with extensive simulation results. It is shown that our robust design achieves significant performance gain compared to the naive beamforming approaches and considerably outperforms the robust Half-Duplex (HD) system.