Title :
An upper bound on the back-up depth for maximum likelihood decoding of convolutional codes (Corresp.)
fDate :
5/1/1976 12:00:00 AM
Abstract :
By using distance properties of convolutional codes, an upper bound on the back-up depth for maximum likelihood decoding is derived. Then several constraints for performing the back-up search are introduced which eliminate the necessity for many of the subsearches. Examples are given in each step to explain the approach.
Keywords :
Convolutional codes; maximum-likelihood (ML) decoding; Convolutional codes; Delay systems; Differential equations; Feedback; Kalman filters; Maximum likelihood decoding; Polynomials; Seminars; Transfer functions; Upper bound;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.1976.1055545