A New Wireless Communication Paradigm through Software-controlled Metasurfaces
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Abstract (arXiv)
Electromagnetic waves undergo multiple uncontrollable alterations as they propagate within a wireless environment. Free space path loss, signal absorption, as well as reflections, refractions and diffractions caused by physical objects within the environment highly affect the performance of wireless communications. Currently, such effects are intractable to account for and are treated as probabilistic factors. The paper proposes a radically different approach, enabling deterministic, programmable control over the behavior of the wireless environments. The key-enabler is the so-called HyperSurface tile, a novel class of planar meta-materials which can interact with impinging electromagnetic waves in a controlled manner. The HyperSurface tiles can effectively re-engineer electromagnetic waves, including steering towards any desired direction, full absorption, polarization manipulation and more. Multiple tiles are employed to coat objects such as walls, furniture, overall, any objects in the indoor and outdoor environments. An external software service calculates and deploys the optimal interaction types per tile, to best fit the needs of communicating devices. Evaluation via simulations highlights the potential of the new concept.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Jun 2018.
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Citing papers per year: 2021: 4; 2022: 3; 2023: 0; 2024: 0; 2025: 0; 2026: 2.
9 papers.
- 2022Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfacescited by 12
- 2021Multi-hop RIS-Empowered Terahertz Communications: A DRL-based Hybrid Beamforming Designcited by 10
- 2021Deep Learning Assisted Calibrated Beam Training for Millimeter-Wave Communication Systemscited by 5
- 2021A Robust Deep Learning-Based Beamforming Design for RIS-assisted Multiuser MISO Communications with Practical Constraintscited by 3
- 2021Covert Communications via Adversarial Machine Learning and Reconfigurable Intelligent Surfacescited by 0
- 2022Reconfigurable Intelligent Surface Enabled Spatial Multiplexing with Fully Convolutional Networkcited by 0
- 2022Phase Shift Design in RIS Empowered Wireless Networks: From Optimization to AI-Based Methodscited by 0
- 2026A novel RF-enabled Non-Destructive Inspection Method through Machine Learning and Programmable Wireless Environmentscited by 0
- 2026Diffusion-Based Inverse Design of Dielectric Resonator Metasurfaces for Shaping Smart Electromagnetic Environmentscited by 0
- 2026Diffusion-Based Inverse Design of Dielectric Resonator Metasurfaces for Shaping Smart Electromagnetic Environments30 Aug 2026
- 2026A novel RF-enabled Non-Destructive Inspection Method through Machine Learning and Programmable Wireless Environments10 Jan 2026
- 2022Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfaces8 May 2022
- 2022Phase Shift Design in RIS Empowered Wireless Networks: From Optimization to AI-Based Methods28 Apr 2022
- 2022Reconfigurable Intelligent Surface Enabled Spatial Multiplexing with Fully Convolutional Network8 Jan 2022
- 2021Covert Communications via Adversarial Machine Learning and Reconfigurable Intelligent Surfaces21 Dec 2021
- 2021A Robust Deep Learning-Based Beamforming Design for RIS-assisted Multiuser MISO Communications with Practical Constraints12 Nov 2021
- 2021Multi-hop RIS-Empowered Terahertz Communications: A DRL-based Hybrid Beamforming Design22 Jan 2021
- 2021Deep Learning Assisted Calibrated Beam Training for Millimeter-Wave Communication Systems8 Jan 2021