Efficient IRS Selection Scheme in Multi-IRS-Aided Wireless Networks

We propose an efficient intelligent reflecting surface (IRS) selection scheme in multi-IRS-aided wireless networks. Unlike conventional methods assigning dedicated resources per IRS for straightforward channel quality estimation, our approach employs a shared resource set for all IRSs. Leveraging th...

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Bibliographic Details
Published inIEEE wireless communications letters p. 1
Main Authors Kwon, Doyle, Kim, Duk Kyung
Format Journal Article
LanguageEnglish
Published IEEE 05.08.2024
Subjects
Channel estimation
Discrete Fourier transforms
Estimation
Intelligent reflecting surface (IRS)
IRS selection algorithm
Reflection
Sparse signal recovery problem (SSRP)
Spectral efficiency
Vectors
Wireless networks
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Summary:We propose an efficient intelligent reflecting surface (IRS) selection scheme in multi-IRS-aided wireless networks. Unlike conventional methods assigning dedicated resources per IRS for straightforward channel quality estimation, our approach employs a shared resource set for all IRSs. Leveraging the sparse signal recovery problem (SSRP) in simultaneously reflected signals by IRSs, we devise a computationally efficient IRS selection algorithm to find the optimal IRS with the best cascaded channel quality. The proposed scheme achieves over 98% accuracy in selecting the optimal IRS when there are fewer than 11 IRSs with spectral efficiency only 1.5% lower than the ideal scheme.
ISSN:2162-2337
2162-2345
DOI:10.1109/LWC.2024.3438838