BEAST decoding of block codes obtained via convolutional codes

Author

Bocharova, Irina E. ; Handlery, Marc ; Johannesson, Rolf ; Kudryashov, Boris D.

Author_Institution

Dept. of Inf. Technol., Lund Univ., Sweden

Volume

51

Issue

5

fYear

2005

fDate

5/1/2005 12:00:00 AM

Firstpage

1880

Lastpage

1891

Abstract

BEAST is a bidirectional efficient algorithm for searching trees. In this correspondence, BEAST is extended to maximum-likelihood (ML) decoding of block codes obtained via convolutional codes. First it is shown by simulations that the decoding complexity of BEAST is significantly less than that of the Viterbi algorithm. Then asymptotic upper bounds on the BEAST decoding complexity for three important ensembles of codes are derived. They verify BEAST´s high efficiency compared to other algorithms. For high rates, the new asymptotic bound for the best ensemble is in fact better than previously known bounds.

Keywords

block codes; convolutional codes; maximum likelihood decoding; tree searching; BEAST; asymptotic upper bound; asymptotical decoding complexity; bidirectional efficient algorithm; block codes; convolutional codes; maximum-likelihood decoding; tree search; Block codes; Convolutional codes; Councils; Encoding; Information systems; Information technology; Maximum likelihood decoding; Tail; Upper bound; Viterbi algorithm; Asymptotical decoding complexity; bidirectional search of trees; convolutional codes; decoding of block codes; maximum-likelihood (ML) decoding;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/TIT.2005.846448

Filename

1424329