Weiss–Weinstein Bound for Data-Aided Carrier Estimation

Author

Renaux, Alexandre

Author_Institution

SATIE Lab., Ecole Normale Superieure of Cachan

Volume

14

Issue

4

fYear

2007

fDate

4/1/2007 12:00:00 AM

Firstpage

283

Lastpage

286

Abstract

This letter investigates Bayesian bounds on the mean-square error (MSE) applied to a data-aided carrier estimation problem. The presented bounds are derived from a covariance inequality principle: the so-called Weiss and Weinstein family. These bounds are of utmost interest to find the fundamental MSE limits of an estimator, even for critical scenarios (low signal-to-noise ratio and/or low number of observations). In a data-aided carrier estimation problem, a closed-form expression of the Weiss-Weinstein bound (WWB) that is known to be the tightest bound of the Weiss and Weinstein family is given. A comparison with the maximum likelihood estimator and the other bounds of the Weiss and Weinstein family is given. The WWB is shown to be an efficient tool to approximate this estimator´s MSE and to predict the well-known threshold effect

Keywords

covariance analysis; mean square error methods; Bayesian bound; MSE; WWB; Weiss-Weinstein bound; covariance inequality principle; data-aided carrier estimation; mean-square error; Array signal processing; Bayesian methods; Closed-form solution; Digital communication; Digital signal processing; Frequency estimation; Maximum likelihood estimation; Random variables; Signal to noise ratio; Spectral analysis; Carrier frequency estimation; Weiss and Weinstein family bounds; estimators performance;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2006.887782

Filename

4130406