Tree search algorithms for self-adaptive maximum-likelihood sequence estimation

Author

Paris, Bernd-Peter ; Shah, Ali R.

Author_Institution

Dept. of Electr. & Comput. Eng., George Mason Univ., Fairfax, VA, USA

fYear

1995

fDate

17-22 Sep 1995

Firstpage

405

Abstract

The problem of implementing self-adaptive equalization algorithms in real-time is addressed. Self-adaptive equalization determines the transmitted sequence without using a training sequence. We focus our attention on the special case of a discrete-time finite-state Markov process in which a sequence of equally likely symbols s_k drawn from an a discrete and finite alphabet A is input to a channel which introduces intersymbol interference in addition to white Gaussian noise. Simulation results for the self-adaptive tree search procedures based on Fano (1963), stack and M-algorithm are presented

Keywords

Gaussian channels; Markov processes; adaptive equalisers; estimation theory; intersymbol interference; maximum likelihood estimation; tree searching; Fano algorithm; M-algorithm; discrete-time finite-state Markov process; intersymbol interference; real time algorithms; self-adaptive equalization algorithms; self-adaptive maximum-likelihood sequence estimation; simulation results; stack algorithm; training sequence; tree search algorithms; white Gaussian noise channel; Adaptive equalizers; Convolutional codes; Digital communication; Gaussian noise; Laboratories; Markov processes; Maximum likelihood detection; Maximum likelihood estimation; Signal processing; State-space methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Theory, 1995. Proceedings., 1995 IEEE International Symposium on

Conference_Location

Whistler, BC

Print_ISBN

0-7803-2453-6

Type

conf

DOI

10.1109/ISIT.1995.550392

Filename

550392