Data-Aided Signal-to-Noise-Ratio estimation in time selective fading channels

Ami Wiesel; Jason Goldberg; Hagit Messer

doi:10.1109/icassp.2002.5745079

Data-Aided Signal-to-Noise-Ratio estimation in time selective fading channels

Ami Wiesel^*, Jason Goldberg, Hagit Messer

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

3 Scopus citations

Abstract

Data-Aided Signal-to-Noise-Ratio (SNR) estimation is considered for time selective fading channels whose time variation is described by a polynomial time model. The inherent estimation accuracy limitations associated with the problem are quantified via a Cramer-Rao Bound analysis. A maximum likelihood type class of estimators is proposed and its exact, non-asymptotic performance is computed. The standard, constant channel SNR estimator performance is determined in the presence of channel polynomial order mismatch. Simulations results are presented which verify the effectiveness of the technique as well as its performance advantage over previously proposed methods.

Original language	English
Pages (from-to)	III/2197-III/2200
Journal	Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Volume	3
DOIs	https://doi.org/10.1109/icassp.2002.5745079
State	Published - 2002
Externally published	Yes
Event	2002 IEEE International Conference on Acoustic, Speech, and Signal Processing - Orlando, FL, United States Duration: 13 May 2002 → 17 May 2002

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title = "Data-Aided Signal-to-Noise-Ratio estimation in time selective fading channels",

abstract = "Data-Aided Signal-to-Noise-Ratio (SNR) estimation is considered for time selective fading channels whose time variation is described by a polynomial time model. The inherent estimation accuracy limitations associated with the problem are quantified via a Cramer-Rao Bound analysis. A maximum likelihood type class of estimators is proposed and its exact, non-asymptotic performance is computed. The standard, constant channel SNR estimator performance is determined in the presence of channel polynomial order mismatch. Simulations results are presented which verify the effectiveness of the technique as well as its performance advantage over previously proposed methods.",

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doi = "10.1109/icassp.2002.5745079",

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AU - Goldberg, Jason

AU - Messer, Hagit

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AB - Data-Aided Signal-to-Noise-Ratio (SNR) estimation is considered for time selective fading channels whose time variation is described by a polynomial time model. The inherent estimation accuracy limitations associated with the problem are quantified via a Cramer-Rao Bound analysis. A maximum likelihood type class of estimators is proposed and its exact, non-asymptotic performance is computed. The standard, constant channel SNR estimator performance is determined in the presence of channel polynomial order mismatch. Simulations results are presented which verify the effectiveness of the technique as well as its performance advantage over previously proposed methods.

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T2 - 2002 IEEE International Conference on Acoustic, Speech, and Signal Processing

Y2 - 13 May 2002 through 17 May 2002

ER -

Data-Aided Signal-to-Noise-Ratio estimation in time selective fading channels

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