Rapid Diagnostics of Reconfigurable Intelligent Surfaces Using Space‐Time‐Coding Modulation Article Swipe
Yi Ning Zheng
,
Lei Zhang
,
Xiao Qing Chen
,
Marco Rossi
,
Giuseppe Castaldi
,
Shuo Liu
,
Tie Jun Cui
,
Vincenzo Galdi
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/adfm.202507430
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/adfm.202507430
Reconfigurable intelligent surfaces (RISs) have emerged as a key technology for shaping smart wireless environments in next‐generation wireless communication systems. To support the large‐scale deployment of RISs, a reliable and efficient diagnostic method is essential for maintaining optimal performance. In this work, a robust and effective approach for RIS diagnostics is proposed using a space‐time coding strategy with orthogonal codes. The proposed method encodes the reflected signals from individual RIS elements into distinct code channels, enabling the recovery of channel power at the receiving terminals for fault identification. Theoretical analysis shows that normally functioning elements generate high power in their respective code channels, whereas faulty elements exhibit significantly lower power. This distinction enables rapid and accurate diagnostics of the elements’ operational states through simple signal processing techniques. Simulation results validate the effectiveness of the proposed method, even under high fault ratios and varying receiving angles. Proof‐of‐principle experiments on two RIS prototypes are conducted, implementing two coding strategies: direct and segmented. Experimental results in a realistic scenario confirm the reliability of the diagnostic method, demonstrating its potential for large‐scale RIS deployment in future wireless communication systems and radar applications.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/adfm.202507430
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/adfm.202507430
- OA Status
- hybrid
- Cited By
- 2
- References
- 60
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4412384345
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4412384345Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1002/adfm.202507430Digital Object Identifier
- Title
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Rapid Diagnostics of Reconfigurable Intelligent Surfaces Using Space‐Time‐Coding ModulationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-07-14Full publication date if available
- Authors
-
Yi Ning Zheng, Lei Zhang, Xiao Qing Chen, Marco Rossi, Giuseppe Castaldi, Shuo Liu, Tie Jun Cui, Vincenzo GaldiList of authors in order
- Landing page
-
https://doi.org/10.1002/adfm.202507430Publisher landing page
- PDF URL
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/adfm.202507430Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/adfm.202507430Direct OA link when available
- Concepts
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Materials science, Coding (social sciences), Modulation (music), Nanotechnology, Acoustics, Physics, Mathematics, StatisticsTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2025: 2Per-year citation counts (last 5 years)
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60Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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