DocumentCode :
1525635
Title :
Joint turbo decoding and estimation of hidden Markov sources
Author :
Garcia-Frias, Javier ; Villasenor, John D.
Author_Institution :
Dept. of Electr. & Comput. Eng., Delaware Univ., Newark, DE, USA
Volume :
19
Issue :
9
fYear :
2001
fDate :
9/1/2001 12:00:00 AM
Firstpage :
1671
Lastpage :
1679
Abstract :
We describe a joint source-channel scheme for modifying a turbo decoder in order to exploit the statistical characteristics of hidden Markov sources. The basic idea is to treat the trellis describing the hidden Markov source as another constituent decoder which exchanges information with the other constituent decoder blocks. The source block uses as extrinsic information the probability of the input bits that is provided by the constituent decoder blocks. On the other hand, it produces a new estimation of such a probability which will be used as extrinsic information by the constituent turbo decoders. The proposed joint source-channel decoding technique leads to significantly improved performance relative to systems in which source statistics are not exploited and avoids the need to perform any explicit source coding prior to transmission. Lack of a priori knowledge of the source parameters does not degrade the performance of the system, since these parameters can be jointly estimated with turbo decoding
Keywords :
Markov processes; combined source-channel coding; concatenated codes; decoding; parameter estimation; probability; statistical analysis; turbo codes; decoder blocks; hidden Markov sources; joint estimation; joint source-channel coding; joint turbo decoding; parallel concatenated codes; probability; source block; source parameters; source statistics; statistical characteristics; system performance; trellis; turbo decoder; Degradation; Entropy; Hidden Markov models; Iterative algorithms; Iterative decoding; Probability; Redundancy; Source coding; Statistics; Turbo codes;
fLanguage :
English
Journal_Title :
Selected Areas in Communications, IEEE Journal on
Publisher :
ieee
ISSN :
0733-8716
Type :
jour
DOI :
10.1109/49.947032
Filename :
947032
Link To Document :
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