Analytical approach to low-density convolutional codes

Author

Engdahl, K. ; Lentmaier, M. ; Truhachev, D.V. ; Zigangirov, K.

Author_Institution

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

fYear

2000

fDate

2000

Firstpage

201

Abstract

A statistical analysis of low-density convolutional (LDC) codes is performed. This analysis is based on the consideration of a special statistical ensemble of Markov scramblers and the solution to a system of recurrent equations describing this ensemble. The results of the analysis are lower bounds for the free distance of the codes and upper bounds for the maximum likelihood decoding error probability. For the case where the size of the scrambler tends to infinity some asymptotic bounds for the free distance and the error probability are derived. Simulation results for iterative decoding of LDC codes are also presented

Keywords

Markov processes; convolutional codes; error statistics; iterative decoding; maximum likelihood decoding; statistical analysis; Markov scramblers; analytical approach; asymptotic bounds; error probability; free distance; iterative decoding; low-density convolutional codes; lower bounds; maximum likelihood decoding; recurrent equations; statistical analysis; statistical ensemble; upper bounds; Convolution; Convolutional codes; Error probability; Information analysis; Information technology; Iterative decoding; Parity check codes; Performance analysis; Statistical analysis; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Theory, 2000. Proceedings. IEEE International Symposium on

Conference_Location

Sorrento

Print_ISBN

0-7803-5857-0

Type

conf

DOI

10.1109/ISIT.2000.866499

Filename

866499