# Phase Shift Design in RIS Empowered Wireless Networks: From Optimization to AI-Based Methods

arXiv: https://arxiv.org/abs/2204.13372 · HTML: https://mlsanity.com/paper/2204.13372/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 31 of its 66 references that are in the map.
- First posted on arXiv 28 Apr 2022.

## Builds on (most cited first, 30 of 31)

- [CARLA: An Open Urban Driving Simulator](https://mlsanity.com/paper/1711.03938/) (2017)
- [Graph Neural Networks for Scalable Radio Resource Management: Architecture Design and Theoretical Analysis](https://mlsanity.com/paper/2007.07632/) (2020)
- [Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming](https://mlsanity.com/paper/1810.03961/) (2018)
- [Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning](https://mlsanity.com/paper/2002.10072/) (2020)
- [Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network](https://mlsanity.com/paper/1905.00152/) (2019)
- [Wireless Communications Through Reconfigurable Intelligent Surfaces](https://mlsanity.com/paper/1906.09490/) (2019)
- [Intelligent Reflecting Surface Aided Wireless Communications: A Tutorial](https://mlsanity.com/paper/2007.02759/) (2020)
- [Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless Communications](https://mlsanity.com/paper/2002.12271/) (2020)
- [Holographic MIMO Surfaces for 6G Wireless Networks: Opportunities, Challenges, and Trends](https://mlsanity.com/paper/1911.12296/) (2019)
- [Edge Federated Learning Via Unit-Modulus Over-The-Air Computation](https://mlsanity.com/paper/2101.12051/) (2021)
- [Hybrid Beamforming for Reconfigurable Intelligent Surface based Multi-user Communications: Achievable Rates with Limited Discrete Phase Shifts](https://mlsanity.com/paper/1910.14328/) (2019)
- [Intelligent Reflecting Surface: Practical Phase Shift Model and Beamforming Optimization](https://mlsanity.com/paper/1907.06002/) (2019)
- [Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface with Discrete Phase Shifts](https://mlsanity.com/paper/1906.03165/) (2019)
- [Unsupervised Learning for Passive Beamforming](https://mlsanity.com/paper/2001.02348/) (2020)
- [Heterogeneous Transformer: A Scale Adaptable Neural Network Architecture for Device Activity Detection](https://mlsanity.com/paper/2112.10086/) (2021)
- [A New Wireless Communication Paradigm through Software-controlled Metasurfaces](https://mlsanity.com/paper/1806.01792/) (2018)
- [Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces](https://mlsanity.com/paper/1912.01497/) (2019)
- [Reconfigurable Intelligent Surfaces for Wireless Communications: Overview of Hardware Designs, Channel Models, and Estimation Techniques](https://mlsanity.com/paper/2203.03176/) (2022)
- [A Framework for One-Bit and Constant-Envelope Precoding over Multiuser Massive MISO Channels](https://mlsanity.com/paper/1810.03159/) (2018)
- [Reconfigurable Intelligent Surfaces vs. Relaying: Differences, Similarities, and Performance Comparison](https://mlsanity.com/paper/1908.08747/) (2019)
- [Neural Calibration for Scalable Beamforming in FDD Massive MIMO with Implicit Channel Estimation](https://mlsanity.com/paper/2108.01529/) (2021)
- [Reconfigurable Intelligent Surface for Green Edge Inference](https://mlsanity.com/paper/1912.00820/) (2019)
- [Channel Estimation and Passive Beamforming for Intelligent Reflecting Surface: Discrete Phase Shift and Progressive Refinement](https://mlsanity.com/paper/1912.10646/) (2019)
- [Intelligent Reflecting Surface: A Programmable Wireless Environment for Physical Layer Security](https://mlsanity.com/paper/1905.03689/) (2019)
- [Weighted Sum-Rate Optimization for Intelligent Reflecting Surface Enhanced Wireless Networks](https://mlsanity.com/paper/1905.07920/) (2019)
- [Joint Active and Passive Beamforming Optimization for Intelligent Reflecting Surface Assisted SWIPT under QoS Constraints](https://mlsanity.com/paper/1910.06220/) (2019)
- [Intelligent Reflecting Surface Aided MISO Uplink Communication Network: Feasibility and Power Minimization for Perfect and Imperfect CSI](https://mlsanity.com/paper/2011.11856/) (2020)
- [Reconfigurable Intelligent Surface Aided Mobile Edge Computing: From Optimization-Based to Location-Only Learning-Based Solutions](https://mlsanity.com/paper/2102.07384/) (2021)
- [Physical Layer Security Enhancement Exploiting Intelligent Reflecting Surface](https://mlsanity.com/paper/1911.02766/) (2019)
- [Robust and Secure Beamforming for Intelligent Reflecting Surface Aided mmWave MISO Systems](https://mlsanity.com/paper/2003.11195/) (2020)

## Abstract (arXiv)

Reconfigurable intelligent surfaces (RISs) have a revolutionary capability to customize the radio propagation environment for wireless networks. To fully exploit the advantages of RISs in wireless systems, the phases of the reflecting elements must be jointly designed with conventional communication resources, such as beamformers, transmit power, and computation time. However, due to the unique constraints on the phase shift, and massive numbers of reflecting units and users in large-scale networks, the resulting optimization problems are challenging to solve. This paper provides a review of current optimization methods and artificial intelligence-based methods for handling the constraints imposed by RIS and compares them in terms of solution quality and computational complexity. Future challenges in phase shift optimization involving RISs are also described and potential solutions are discussed.