DocumentCode :
1192529
Title :
To code, or not to code: lossy source-channel communication revisited
Author :
Gastpar, Michael ; Rimoldi, Bixio ; Vetterli, Martin
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of California, Berkeley, CA, USA
Volume :
49
Issue :
5
fYear :
2003
fDate :
5/1/2003 12:00:00 AM
Firstpage :
1147
Lastpage :
1158
Abstract :
What makes a source-channel communication system optimal? It is shown that in order to achieve an optimal cost-distortion tradeoff, the source and the channel have to be matched in a probabilistic sense. The match (or lack of it) involves the source distribution, the distortion measure, the channel conditional distribution, and the channel input cost function. Closed-form necessary and sufficient expressions relating the above entities are given. This generalizes both the separation-based approach as well as the two well-known examples of optimal uncoded communication. The condition of probabilistic matching is extended to certain nonergodic and multiuser scenarios. This leads to a result on optimal single-source broadcast communication.
Keywords :
broadcast channels; codes; combined source-channel coding; decoding; multiuser channels; optimisation; probability; channel conditional distribution; channel input cost function; channel input symbol; closed-form necessary expression; closed-form sufficient expression; communication; decoder; distortion measure; encoder; joint source-channel coding; lossy source-channel communication; multiuser communication; nonergodic scenario; optimal cost-distortion tradeoff; optimal single-source broadcast communication; optimal uncoded communication; probabilistic matching; separation-based approach; single-letter codes; source distribution; source output symbol; source reconstruction symbol; source-channel communication system; AWGN; Associate members; Broadcasting; Channel coding; Communication systems; Cost function; Delay; Distortion measurement; Information theory; Loss measurement;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2003.810631
Filename :
1197846
Link To Document :
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