Sequence estimation in the presence of random parameters via the EM algorithm

Author

Georghiades, Costas N. ; Han, Jae Choong

Author_Institution

Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA

Volume

45

Issue

3

fYear

1997

fDate

3/1/1997 12:00:00 AM

Firstpage

300

Lastpage

308

Abstract

The expectation-maximization (EM) algorithm was first introduced in the statistics literature as an iterative procedure that under some conditions produces maximum-likelihood (hit) parameter estimates. In this paper we investigate the application of the EM algorithm to sequence estimation in the presence of random disturbances and additive white Gaussian noise. As examples of the use of the EM algorithm, we look at the random-phase and fading channels, and show that a formulation of the sequence estimation problem based on the EM algorithm can provide a means of obtaining ML sequence estimates, a task that has been previously too complex to perform

Keywords

Gaussian noise; fading; iterative methods; maximum likelihood estimation; optimisation; random noise; sequential estimation; telecommunication channels; white noise; EM algorithm; additive white Gaussian noise; expectation-maximization algorithm; fading channels; iterative procedure; maximum-likelihood parameter estimates; random disturbances; random parameters; random-phase channels; sequence estimation; Additive noise; Additive white noise; Fading; Gaussian noise; Iterative algorithms; Maximum likelihood estimation; Parameter estimation; Phase estimation; Phase modulation; Statistics;

fLanguage

English

Journal_Title

Communications, IEEE Transactions on

Publisher

ieee

ISSN

0090-6778

Type

jour

DOI

10.1109/26.558691

Filename

558691