Title :
Universally optimum block codes and convolutional codes with maximum likelihood decoding
Author :
Hashimoto, Takeshi ; Arimoto, Suguru
fDate :
5/1/1980 12:00:00 AM
Abstract :
A new proof is presented for the existence of block codes whose error probability under maximum likelihood decoding is bounded asymptotically by the random coding bound universally over all discrete memoryless channels. On the basis of this result, the existence of convolutional codes with universally optimum performance is shown. Furthermore the existence of block codes which attain the expurgated bound universally over all discrete memoryless channels is proved under the use of maximum likelihood decoding.
Keywords :
Block codes; Convolutional codes; maximum-likelihood (ML) decoding; Block codes; Channel coding; Convolutional codes; Error probability; Information theory; Maximum likelihood decoding; Memoryless systems; Mutual information; Viterbi algorithm;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.1980.1056174