Title :
Upper bounds on the number of errors corrected by a convolutional code
Author_Institution :
Tech. Univ. of Denmark, Lyngby, Denmark
Abstract :
We derive upper bounds on the weights of error patterns that can be corrected by a convolutional code with given parameters, or equivalently we give bounds on the code rate for a given set of error patterns. The bounds parallel the Hamming bound for block codes by relating the number of error patterns to the number of distinct syndromes.
Keywords :
block codes; convolutional codes; error correction; error correction codes; maximum likelihood decoding; Hamming bound; ML decoding; binary code; block codes; code rate; convolutional code; error correction; error pattern weight upper bounds; maximum-likelihood decoding; Block codes; Convolutional codes; Error correction; Error correction codes; Linear code; Maximum likelihood decoding; Maximum likelihood estimation; Upper bound;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2003.822600
