An Analytical Characterization of Maximum Likelihood Signal-to-Noise Ratio Estimation

Author

Cioni, Stefano ; Corazza, Giovanni E. ; Bousquet, Michel

Author_Institution

DEIS/ARCES, Bologna Univ.

fYear

2005

fDate

7-7 Sept. 2005

Firstpage

827

Lastpage

830

Abstract

In this work, the maximum-likelihood estimation of the signal-to-noise ratio is analytically characterized. In particular, the useful and the noise power are modelled by a X²-distribution, whereas the resulting signal-to-noise ratio is described in items of a non-central F-distribution. In addition, to better evaluate the estimator efficiency, the Cramer-Rao bound is computed. Finally, in order to completely verify the analytical characterization, the transmit-receive chain has been simulated, and the numerical results are compared to the analytical formulas

Keywords

Gaussian processes; fading channels; maximum likelihood estimation; random processes; signal processing; Cramer-Rao bound; X²-distribution; channel fading; maximum likelihood signal-to-noise ratio estimation; noncentral F-distribution; signal-to-noise ratio; transmit-receive chain; white Gaussian random process; Additive white noise; Analysis of variance; Analytical models; Computational modeling; Gaussian noise; Interference; Maximum likelihood detection; Maximum likelihood estimation; Signal analysis; Signal to noise ratio; χ; Cramer-Rao bound; F-distribution; SNR Estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communication Systems, 2005. 2nd International Symposium on

Conference_Location

Siena

Print_ISBN

0-7803-9206-X

Type

conf

DOI

10.1109/ISWCS.2005.1547825

Filename

1547825