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

arXiv 2204.13372 ↗First posted 28 Apr 2022cs.LGcited by 0

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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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 31 of its 66 references that are in the map. First posted on arXiv 28 Apr 2022.

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31 of 66 references.

References · 31

  1. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  2. 2020Graph Neural Networks for Scalable Radio Resource Management: Architecture Design and Theoretical Analysiscited by 80
  3. 2018Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamformingcited by 41
  4. 2020Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learningcited by 38
  5. 2019Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Networkcited by 35
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  7. 2020Intelligent Reflecting Surface Aided Wireless Communications: A Tutorialcited by 26
  8. 2020Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless Communicationscited by 21
  9. 2019Holographic MIMO Surfaces for 6G Wireless Networks: Opportunities, Challenges, and Trendscited by 20
  10. 2021Edge Federated Learning Via Unit-Modulus Over-The-Air Computationcited by 16
  11. 2019Intelligent Reflecting Surface: Practical Phase Shift Model and Beamforming Optimizationcited by 13
  12. 2019Hybrid Beamforming for Reconfigurable Intelligent Surface based Multi-user Communications: Achievable Rates with Limited Discrete Phase Shiftscited by 12
19 more
  1. 2020Unsupervised Learning for Passive Beamformingcited by 11
  2. 2019Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface with Discrete Phase Shiftscited by 10
  3. 2021Heterogeneous Transformer: A Scale Adaptable Neural Network Architecture for Device Activity Detectioncited by 10
  4. 2018A New Wireless Communication Paradigm through Software-controlled Metasurfacescited by 9
  5. 2019Robust and Secure Wireless Communications via Intelligent Reflecting Surfacescited by 9
  6. 2022Reconfigurable Intelligent Surfaces for Wireless Communications: Overview of Hardware Designs, Channel Models, and Estimation Techniquescited by 7
  7. 2019Reconfigurable Intelligent Surfaces vs. Relaying: Differences, Similarities, and Performance Comparisoncited by 5
  8. 2019Reconfigurable Intelligent Surface for Green Edge Inferencecited by 5
  9. 2021Neural Calibration for Scalable Beamforming in FDD Massive MIMO with Implicit Channel Estimationcited by 5
  10. 2018A Framework for One-Bit and Constant-Envelope Precoding over Multiuser Massive MISO Channelscited by 3
  11. 2019Intelligent Reflecting Surface: A Programmable Wireless Environment for Physical Layer Securitycited by 3
  12. 2019Weighted Sum-Rate Optimization for Intelligent Reflecting Surface Enhanced Wireless Networkscited by 3
  13. 2019Channel Estimation and Passive Beamforming for Intelligent Reflecting Surface: Discrete Phase Shift and Progressive Refinementcited by 3
  14. 2020Intelligent Reflecting Surface Aided MISO Uplink Communication Network: Feasibility and Power Minimization for Perfect and Imperfect CSIcited by 3
  15. 2021Reconfigurable Intelligent Surface Aided Mobile Edge Computing: From Optimization-Based to Location-Only Learning-Based Solutionscited by 3
  16. 2019Joint Active and Passive Beamforming Optimization for Intelligent Reflecting Surface Assisted SWIPT under QoS Constraintscited by 2
  17. 2019Physical Layer Security Enhancement Exploiting Intelligent Reflecting Surfacecited by 2
  18. 2020Robust and Secure Beamforming for Intelligent Reflecting Surface Aided mmWave MISO Systemscited by 1
  19. 2020A Low-Complexity Algorithmic Framework for Large-Scale IRS-Assisted Wireless Systemscited by 1

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