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 journalConference articlepeer-review

3 Scopus citations


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 languageEnglish
Pages (from-to)III/2197-III/2200
JournalProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
StatePublished - 2002
Event2002 IEEE International Conference on Acoustic, Speech, and Signal Processing - Orlando, FL, United States
Duration: 13 May 200217 May 2002


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