# Sum Rate Optimization for Two Way Communications with Intelligent Reflecting Surface

arXiv: https://arxiv.org/abs/2003.00918 · HTML: https://mlsanity.com/paper/2003.00918/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Mar 2020.

## Built on by (most cited first, 3 of 3)

- [Channel Estimation and Hybrid Architectures for RIS-Assisted Communications](https://mlsanity.com/paper/2104.07115/) (2021)
- [Geometry Aware Meta-Learning Neural Network for Joint Phase and Precoder Optimization in RIS](https://mlsanity.com/paper/2409.11270/) (2024)
- [Multi-beam Beamforming in RIS-aided MIMO Subject to Reradiation Mask Constraints -- Optimization and Machine Learning Design](https://mlsanity.com/paper/2507.15367/) (2025)

## Abstract (arXiv)

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.