Beamforming Optimization for IRS-Aided Communications with Transceiver Hardware Impairments

TL;DR

This paper develops a robust beamforming optimization framework for IRS-assisted multi-antenna communications considering practical transceiver hardware impairments, demonstrating improved performance over traditional schemes.

Contribution

It introduces a joint beamforming design method that accounts for hardware impairments, including a closed-form solution and a low-complexity algorithm for IRS reflect beamforming.

Findings

Proposed method outperforms conventional schemes under hardware impairments.

IRS deployment yields significant performance gains even with hardware impairments.

The approach enhances robustness of IRS-assisted communications.

Abstract

In this paper, we focus on intelligent reflecting surface (IRS) assisted multi-antenna communications with transceiver hardware impairments encountered in practice. In particular, we aim to maximize the received signal-to-noise ratio (SNR) taking into account the impact of hardware impairments, where the source transmit beamforming and the IRS reflect beamforming are jointly designed under the proposed optimization framework. To circumvent the non-convexity of the formulated design problem, we first derive a closed-form optimal solution to the source transmit beamforming. Then, for the optimization of IRS reflect beamforming, we obtain an upper bound to the optimal objective value via solving a single convex problem. A low-complexity minorization-maximization (MM) algorithm was developed to approach the upper bound. Simulation results demonstrate that the proposed beamforming design is more robust to the hardware impairments than that of the conventional SNR maximized scheme. Moreover, compared to the scenario without deploying an IRS, the performance gain brought by incorporating the hardware impairments is more evident for the IRS-aided communications.