Sum Rate Optimization for Two Way Communications with Intelligent Reflecting Surface

TL;DR

This paper proposes a method to maximize the sum rate in IRS-enhanced full-duplex MIMO two-way systems by jointly optimizing precoders and IRS phase shifts, considering practical constraints.

Contribution

It introduces an efficient alternating optimization approach for joint precoder and IRS phase shift design, including discrete phase shifts, for improved two-way communication performance.

Findings

The proposed scheme converges quickly and enhances sum rate.

Closed-form solutions enable efficient optimization.

Practical IRS constraints are effectively incorporated.

Abstract

In this letter, an intelligent reflecting surface (IRS) enhanced full-duplex MIMO two-way communication system is studied. The system sum rate is maximized through jointly optimizing the source precoders and the IRS phase shift matrix. Adopting the idea of Arimoto-Blahut algorithm, the non-convex optimization problem is decoupled into three sub-problems, which are solved alternatingly. All the sub-problems can be solved efficiently with closed-form solutions. In addition, practical IRS assumptions, e.g., discrete phase shift levels, are also considered. Numerical results verify the convergence and performance of the proposed scheme.