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Optimal Configuration of Reconfigurable Intelligent Surfaces With Non-uniform Phase Quantization

arXiv 2405.06967 ↗First posted 11 May 2024cs.IT eess.SP math.ITcited by 0

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Abstract (arXiv)

The existing methods for reconfigurable intelligent surface (RIS) beamforming in wireless communications are typically limited to uniform phase quantization. However, in practical applications, engineering challenges and design requirements often lead to non-uniform phase and bit resolution of RIS units, which limits the performance potential of these methods. To address this issue, this paper pioneers the study of discrete non-uniform phase configuration in RIS-assisted multiple-input single-output (MISO) communication and formulates an optimization model to characterize the problem. For single-user scenarios, the paper proposes a partition-andtraversal (PAT) algorithm that efficiently achieves the global optimal solution through systematic search and traversal. For larger-scale multi-user scenarios, aiming to balance performance and computational complexity, an enhanced PAT-based algorithm (E-PAT) is developed. By optimizing the search strategy, the E-PAT algorithm significantly reduces computational overhead and achieves linear complexity. Numerical simulations confirm the effectiveness and superiority of the proposed PAT and EPAT algorithms. Additionally, we provide a detailed analysis of the impact of non-uniform phase quantization on system performance.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 19 of its 39 references that are in the map. First posted on arXiv 11 May 2024.

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19 of 39 references.

References · 19

  1. 2019Wireless Communications Through Reconfigurable Intelligent Surfacescited by 37
  2. 2020Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Aheadcited by 28
  3. 2019Hybrid Beamforming for Reconfigurable Intelligent Surface based Multi-user Communications: Achievable Rates with Limited Discrete Phase Shiftscited by 15
  4. 2019Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface with Discrete Phase Shiftscited by 12
  5. 2019Latency Minimization for Intelligent Reflecting Surface Aided Mobile Edge Computingcited by 11
  6. 2023Intelligent Surfaces Empowered Wireless Network: Recent Advances and The Road to 6Gcited by 9
  7. 2020Reconfigurable Intelligent Surfaces for Localization: Position and Orientation Error Boundscited by 6
  8. 2022Optimal Discrete Beamforming of RIS-Aided Wireless Communications: An Inner Product Maximization Approachcited by 3
  9. 2022A Linear Time Algorithm for the Optimal Discrete IRS Beamformingcited by 3
  10. 2019Robust Beamforming Design for Intelligent Reflecting Surface Aided MISO Communication Systemscited by 2
  11. 2021Configuring Intelligent Reflecting Surface with Performance Guarantees: Optimal Beamformingcited by 2
  12. 2022IRS Aided MEC Systems with Binary Offloading: A Unified Framework for Dynamic IRS Beamformingcited by 2
7 more
  1. 2022Secure Intelligent Reflecting Surface Aided Integrated Sensing and Communicationcited by 2
  2. 2022A Novel SCA-Based Method for Beamforming Optimization in IRS/RIS-Assisted MU-MISO Downlinkcited by 2
  3. 2020Optimal Beamforming for MISO Communications via Intelligent Reflecting Surfacescited by 1
  4. 2021Optimizing a Binary Intelligent Reflecting Surface for OFDM Communications under Mutual Couplingcited by 1
  5. 2023Design of Reconfigurable Intelligent Surfaces for Wireless Communication: A Reviewcited by 1
  6. 2023Intelligent Reflecting Surface Assisted Localization: Performance Analysis and Algorithm Designcited by 1
  7. 2023Optimal Configuration of Reconfigurable Intelligent Surfaces with Arbitrary Discrete Phase Shiftscited by 1

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  1. 2023Quantized Phase Alignment by Discrete Phase Shifts for Reconfigurable Intelligent Surface-Assisted Communication Systems
  2. 2025Discrete Beamforming Optimization for RISs with a Limited Phase Range and Amplitude Attenuation
  3. 2023Multi-User Reconfigurable Intelligent Surface-Aided Communications Under Discrete Phase Shifts ↗
  4. 2024Optimal Beamforming of RIS-Aided Wireless Communications: An Alternating Inner Product Maximization Approach
  5. 2021Optimization of Quantized Phase Shifts for Reconfigurable Smart Surfaces Assisted Communications ↗
  6. 2021A Robust Deep Learning-Based Beamforming Design for RIS-assisted Multiuser MISO Communications with Practical Constraints
  7. 2026Geometry-Informed Optimization of Binary RIS Configurations for Communication and Sensing
  8. 2023Transmitting Data Through Reconfigurable Intelligent Surface: A Spatial Sigma-Delta Modulation Approach