Multi-Scale Channel Estimation for Transmissive RIS Transceivers via Partial Active Elements

We propose a two-stage channel estimation protocolfor partially active transmissive reconfigurable intelligentsurface (RIS) transceivers. Local estimates of the quasi-staticfeed antenna--RIS channel are reused during RIS--user trainingto reduce repeated pilot overhead. A multi-scale orthogonal matching pursuit (OMP) algorithm reconstructs both full-dimensional channels through coarse-to-fine dictionary searches. Numerical results show that the proposed method outperforms interpolation baselines and approaches conventional OMP accuracy with reduced dictionary-search cost.Training-length evaluation demonstrates diminishing accuracy gains from longer training, supporting a trade-off between reconstruction accuracy and training overhead.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-16
DOI
https://doi.org/10.5281/zenodo.23407564
Primary Topic
Advanced Wireless Communication Technologies
Type
article
Field-Weighted Citation Impact
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article

Multi-Scale Channel Estimation for Transmissive RIS Transceivers via Partial Active Elements

Shunqing Zhang, 孙彦赞 Sun Yanzan, Qingqing Wu, Kai Cao et al.
Zenodo (CERN European Organization for Nuclear Research)
Advanced Wireless Communication Technologies
article

Multi-Scale Channel Estimation for Transmissive RIS Transceivers via Partial Active Elements

Shunqing Zhang, 孙彦赞 Sun Yanzan, Qingqing Wu, Kai Cao, Xiaojing Chen, Jihong Li, Wen Chen, Chaofan Qiao
article en

Abstract

We propose a two-stage channel estimation protocolfor partially active transmissive reconfigurable intelligentsurface (RIS) transceivers. Local estimates of the quasi-staticfeed antenna--RIS channel are reused during RIS--user trainingto reduce repeated pilot overhead. A multi-scale orthogonal matching pursuit (OMP) algorithm reconstructs both full-dimensional channels through coarse-to-fine dictionary searches. Numerical results show that the proposed method outperforms interpolation baselines and approaches conventional OMP accuracy with reduced dictionary-search cost.Training-length evaluation demonstrates diminishing accuracy gains from longer training, supporting a trade-off between reconstruction accuracy and training overhead.

Zenodo (CERN European Organization for Nuclear Research)
Shanghai University (CN), Shanghai Jiao Tong University (CN)
Openalex Percentile: Top 23%
Advanced Wireless Communication Technologies
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