Title :
An improved method to compute lists of binary vectors that optimize a given weight function with application to soft-decision decoding
Author :
Valembois, Antoine ; Fossorier, Marc
Author_Institution :
Dept. of Electr. Eng., Hawaii Univ., Honolulu, HI, USA
Abstract :
Many algorithms, tree-searching and decoding algorithms in particular, need to generate some lists of binary vectors by increasing value of a given weight function and without omission. To this end, there are not many alternatives to the Dijkstra and the Viterbi algorithm. In this letter a technique suggested by Battail in 1986 to perform this task is reviewed. Then a new technique is deduced from it, that proves to be more efficient than all the others. As an illustration of its good performance we compare a maximum-likelihood-decoding (MLD) algorithm that can be derived from it, with current state-of-the-art complete MLD algorithms for general binary linear codes.
Keywords :
binary codes; linear codes; maximum likelihood decoding; optimisation; tree searching; binary linear codes; binary vectors; maximum-likelihood-decoding algorithm; soft-decision decoding; tree-searching; weight function optimization; Convolutional codes; Decision trees; Hamming weight; Linear code; Maximum likelihood decoding; Optimization methods; Search methods; Vectors; Viterbi algorithm;
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/4234.966032