Title :
Good error-correcting codes based on very sparse matrices
Author :
MacKay, David J C
Author_Institution :
Cavendish Lab., Cambridge Univ., UK
fDate :
29 Jun-4 Jul 1997
Abstract :
We report theoretical and empirical properties of Gallager´s (1963) low density parity check codes on Gaussian channels. It can be proved that, given an optimal decoder, these codes asymptotically approach the Shannon limit. With a practical `belief propagation´ decoder, performance substantially better than that of standard convolutional and concatenated codes can be achieved; indeed the performance is almost as close to the Shannon limit as that of turbo codes
Keywords :
Gaussian channels; decoding; error correction codes; matrix algebra; Gaussian channels; Shannon limit; belief propagation decoder; concatenated codes; convolutional codes; error-correcting codes; low density parity check codes; optimal decoder; performance; turbo codes; very sparse matrices; Belief propagation; Code standards; Concatenated codes; Convolutional codes; Decoding; Error correction codes; Gaussian channels; Parity check codes; Sparse matrices; Turbo codes;
Conference_Titel :
Information Theory. 1997. Proceedings., 1997 IEEE International Symposium on
Conference_Location :
Ulm
Print_ISBN :
0-7803-3956-8
DOI :
10.1109/ISIT.1997.613028