Low-Complexity Robust Beamforming Design for IRS-Aided MISO Systems with Imperfect Channels

TL;DR

This paper proposes a low-complexity robust beamforming method for IRS-assisted MISO systems with imperfect channels, optimizing sum rate via joint active and passive beamforming using a novel PDD algorithm.

Contribution

It introduces a new robust beamforming design that efficiently handles channel uncertainty with closed-form solutions, reducing computational complexity.

Findings

Achieves high system performance with low computational complexity.

Effectively handles channel uncertainty in IRS-assisted MISO systems.

Demonstrates superior sum rate performance through simulations.

Abstract

In this paper, large-scale intelligent reflecting sur-face (IRS)-assisted multiple-input single-output (MISO) system is considered in the presence of channel uncertainty. To maximize the average sum rate of the system by jointly optimizing the active beamforming at the BS and the passive phase shifts at the IRS, while satisfying the power constraints, a novel robust beamforming design is proposed by using the penalty dual decomposition (PDD) algorithm. By applying the upper bound maximization/minimization (BSUM) method, in each iteration of the algorithm, the optimal solution for each variable can be obtained with closed-form expression. Simulation results show that the proposed scheme achieves high performance with very low computational complexity.