Title :
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.
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;
Conference_Titel :
Wireless Communication Systems, 2005. 2nd International Symposium on
Conference_Location :
Siena
Print_ISBN :
0-7803-9206-X
DOI :
10.1109/ISWCS.2005.1547825
