mlsanityData to 7 Oct 2026

Channel Estimation and Hybrid Architectures for RIS-Assisted Communications

arXiv 2104.07115 ↗First posted 14 Apr 2021eess.SP cs.AIcited by 1

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Abstract (arXiv)

Reconfigurable intelligent surfaces (RISs) are considered as potential technologies for the upcoming sixth-generation (6G) wireless communication system. Various benefits brought by deploying one or multiple RISs include increased spectrum and energy efficiency, enhanced connectivity, extended communication coverage, reduced complexity at transceivers, and even improved localization accuracy. However, to unleash their full potential, fundamentals related to RISs, ranging from physical-layer (PHY) modelling to RIS phase control, need to be addressed thoroughly. In this paper, we provide an overview of some timely research problems related to the RIS technology, i.e., PHY modelling (including also physics), channel estimation, potential RIS architectures, and RIS phase control (via both model-based and data-driven approaches), along with recent numerical results. We envision that more efforts will be devoted towards intelligent wireless environments, enabled by RISs.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 40 of its 60 references that are in the map. First posted on arXiv 14 Apr 2021.

Builds on

40 of 60 references.

References · 40

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28 more
  1. 2019Indoor Signal Focusing with Deep Learning Designed Reconfigurable Intelligent Surfacescited by 12
  2. 2019Cascaded Channel Estimation for Large Intelligent Metasurface Assisted Massive MIMOcited by 11
  3. 2020Unsupervised Learning for Passive Beamformingcited by 11
  4. 2019Radio Localization and Mapping with Reconfigurable Intelligent Surfacescited by 10
  5. 2020Channel Estimation for RIS-Aided mmWave MIMO Systems via Atomic Norm Minimizationcited by 9
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  18. 2020Parallel Factor Decomposition Channel Estimation in RIS-Assisted Multi-User MISO Communicationcited by 3
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