An Optimal Channel Estimation Scheme for Intelligent Reflecting Surfaces based on a Minimum Variance Unbiased Estimator

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2 Citationer (Scopus)

Abstrakt

In a wireless system with Intelligent Reflective Surfaces (IRS) containing many passive elements, we consider the problem of channel estimation. All the links from the transmitter to the receiver via each IRS elements (or groups) are estimated. We show that the estimation performance are dependent on the setting of the IRS, and design an optimal channel estimation scheme where the IRS elements follow an optimal series of activation patterns. The optimal design is guided by results for the minimum variance unbiased estimation. The IRS setting during the channel estimation period mimics the discrete Fourier transforms. We show theoretically and with simulations that the estimation variance is one order smaller compared to existing methods with on/off IRS activation patterns as proposed in the literature.
OriginalsprogEngelsk
TitelICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Antal sider5
ForlagIEEE
Publikationsdato9 apr. 2020
Sider5000-5004
Artikelnummer9053695
ISBN (Trykt)978-1-5090-6632-2
ISBN (Elektronisk)978-1-5090-6631-5
DOI
StatusUdgivet - 9 apr. 2020
BegivenhedICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Barcelona, Spanien
Varighed: 4 maj 20208 maj 2020

Konference

KonferenceICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
LandSpanien
ByBarcelona
Periode04/05/202008/05/2020
NavnICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN1520-6149

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  • Citationsformater

    Jensen, T., & De Carvalho, E. (2020). An Optimal Channel Estimation Scheme for Intelligent Reflecting Surfaces based on a Minimum Variance Unbiased Estimator. I ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (s. 5000-5004). [9053695] IEEE. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings https://doi.org/10.1109/ICASSP40776.2020.9053695