Sum Rate Optimization for Two Way Communications with Intelligent Reflecting Surface
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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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Mar 2020.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 1; 2025: 1.
3 papers.
- 2021Channel Estimation and Hybrid Architectures for RIS-Assisted Communicationscited by 1
- 2024Geometry Aware Meta-Learning Neural Network for Joint Phase and Precoder Optimization in RIScited by 0
- 2025Multi-beam Beamforming in RIS-aided MIMO Subject to Reradiation Mask Constraints -- Optimization and Machine Learning Designcited by 0
- 2025Multi-beam Beamforming in RIS-aided MIMO Subject to Reradiation Mask Constraints -- Optimization and Machine Learning Design21 Jul 2025
- 2024Geometry Aware Meta-Learning Neural Network for Joint Phase and Precoder Optimization in RIS17 Sep 2024
- 2021Channel Estimation and Hybrid Architectures for RIS-Assisted Communications14 Apr 2021