Generalized MLSDE via the EM algorithm

Author

Zamiri-Jafarian, H. ; Pasupathy, S.

Author_Institution

Dept. of Electr. & Comput. Eng., Toronto Univ., Ont., Canada

fYear

1999

fDate

6-10 Jun 1999

Firstpage

130

Lastpage

134

Abstract

Generalized maximum likelihood sequence detection and estimation (GMLSDE) is developed in this paper based on the expectation and maximization (EM) algorithm. The GMLSDE couples the estimation of channel parameters and data detection in the framework of the maximum likelihood (ML) criterion and unifies many MLSD/MLSDE structure receivers for different channel models. The GMLSDE clarifies the relation among channel model, receiver structure and degree of optimality. The per-survivor processing (PSP) and per-branch processing (PBP) methods emerge naturally from the EM aspect of the GMLSDE as well

Keywords

adaptive estimation; adaptive signal detection; digital communication; maximum likelihood detection; maximum likelihood sequence estimation; optimisation; receivers; EM algorithm; MLSD/MLSDE structure receivers; adaptive MLSDE receivers; channel models; channel parameter estimation; data detection; digital communications systems; expectation maximization algorithm; generalized MLSDE; generalized maximum likelihood sequence detection; generalized maximum likelihood sequence estimation; maximum likelihood criterion; optimality; per-branch processing; per-survivor processing; Additive noise; Channel estimation; Delay; Error probability; Gaussian noise; Least squares approximation; Maximum likelihood estimation; Parameter estimation; Signal detection; Viterbi algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Theory Mini-Conference, 1999

Conference_Location

Vancouver, BC

Print_ISBN

0-7803-5653-5

Type

conf

DOI

10.1109/CTMC.1999.790251

Filename

790251