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Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead

arXiv 2004.09352 ↗First posted 20 Apr 2020cs.IT eess.SP math.ITcited by 28

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Abstract (arXiv)

What is a reconfigurable intelligent surface? What is a smart radio environment? What is a metasurface? How do metasurfaces work and how to model them? How to reconcile the mathematical theories of communication and electromagnetism? What are the most suitable uses and applications of reconfigurable intelligent surfaces in wireless networks? What are the most promising smart radio environments for wireless applications? What is the current state of research? What are the most important and challenging research issues to tackle? These are a few of the many questions that we investigate in this short opus, which has the threefold objective of introducing the emerging research field of smart radio environments empowered by reconfigurable intelligent surfaces, putting forth the need of reconciling and reuniting C. E. Shannon's mathematical theory of communication with G. Green's and J. C. Maxwell's mathematical theories of electromagnetism, and reporting pragmatic guidelines and recipes for employing appropriate physics-based models of metasurfaces in wireless communications.

Key facts. Cited by 28 papers in the map (data through 13 Oct 2026). First posted on arXiv 20 Apr 2020.

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Cited by year (2026 to 13 Oct)

Citing papers per year: 2021: 5; 2022: 4; 2023: 1; 2024: 7; 2025: 6; 2026: 5.

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  1. 2021Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applicationscited by 97
  2. 2024Deep-Reinforcement-Learning-Based AoI-Aware Resource Allocation for RIS-Aided IoV Networkscited by 12
  3. 2024Reconfigurable Intelligent Surface Assisted VEC Based on Multi-Agent Reinforcement Learningcited by 11
  4. 2022Differentially Private Federated Learning via Reconfigurable Intelligent Surfacecited by 5
  5. 2024Reconfigurable Intelligent Surface Aided Vehicular Edge Computing: Joint Phase-shift Optimization and Multi-User Power Allocationcited by 5
  6. 2021A deep learning approach for inverse design of the metasurface for dual-polarized wavescited by 4
  7. 2021Learning to Estimate RIS-Aided mmWave Channelscited by 4
  8. 2023Localization with Reconfigurable Intelligent Surface: An Active Sensing Approachcited by 3
  9. 2021Channel Estimation and Hybrid Architectures for RIS-Assisted Communicationscited by 1
  10. 2024Meta-Learning Based Optimization for Large Scale Wireless Systemscited by 1
  11. 2025Joint Transmit and Pinching Beamforming for Pinching Antenna Systems (PASS): Optimization-Based or Learning-Based?cited by 1
  12. 2025Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systemscited by 1
16 more
  1. 2025RIS-Assisted Downlink Pinching-Antenna Systems: GNN-Enabled Optimization Approachescited by 1
  2. 2021Beyond 5G RIS mmWave Systems: Where Communication and Localization Meetcited by 0
  3. 2022Reconfigurable Intelligent Surface Enabled Spatial Multiplexing with Fully Convolutional Networkcited by 0
  4. 2022Reconfigurable Intelligent Surface-assisted Classification of Modulations using Deep Learningcited by 0
  5. 2022Deep Reinforcement Learning for IRS Phase Shift Design in Spatiotemporally Correlated Environmentscited by 0
  6. 2024Multi-stream Transmission for Directional Modulation Network via Distributed Multi-UAV-aided Multi-active-IRScited by 0
  7. 2024Optimal Beamforming of RIS-Aided Wireless Communications: An Alternating Inner Product Maximization Approachcited by 0
  8. 2024Optimal Configuration of Reconfigurable Intelligent Surfaces With Non-uniform Phase Quantizationcited by 0
  9. 2025Deep Learning Optimization of Two-State Pinching Antennas Systemscited by 0
  10. 2025Multi-beam Beamforming in RIS-aided MIMO Subject to Reradiation Mask Constraints -- Optimization and Machine Learning Designcited by 0
  11. 2025Towards 6G Intelligence: The Role of Generative AI in Future Wireless Networkscited by 0
  12. 2026Adjustment of Cluster-Then-Predict Framework for Multiport Scatterer Load Predictioncited by 0
  13. 2026Spectral- and Energy-efficient Multi-BS Multi-RIS Pinching-antenna Systems: A GNN-based Approachcited by 0
  14. 2026Optimization Algorithms for Joint OFDM Waveform Design and RIS Configuration in 6G Networks: From Convex Relaxation to Foundation Modelscited by 0
  15. 2026Diffusion-Based Inverse Design of Dielectric Resonator Metasurfaces for Shaping Smart Electromagnetic Environmentscited by 0
  16. 2026A 3GPP-Compliant Benchmark Dataset for RIS-Aided Beyond 5G Networkscited by 0