Title :
Distributed Source Coding Using Raptor Codes for Hidden Markov Sources
Author :
Fresia, M. ; Vandendorpe, L. ; Poor, H.V.
Author_Institution :
Princeton Univ., Princeton
Abstract :
Interest in distributed source coding (DSC) has increased in recent years due to the development of wireless networks. In this paper we propose a solution based on a new rateless class of codes, the Raptor codes. In real applications (where the data source length and the correlation between the sources may vary), rateless codes can be naturally adapted by generating just a single codeword with suitable length. Raptor codes were already considered by Caire et al. (2005) for the lossless compression of a single source.
Keywords :
codes; hidden Markov models; source coding; Raptor codes; codeword; data source length; distributed source coding; hidden Markov sources; lossless compression; source correlation; wireless networks; Bit error rate; Data compression; Entropy; Hidden Markov models; Iterative algorithms; Iterative decoding; Message passing; Redundancy; Source coding; Wireless networks; Distributed Source coding; Hidden Markov model; Raptor codes;
Conference_Titel :
Data Compression Conference, 2008. DCC 2008
Conference_Location :
Snowbird, UT
Print_ISBN :
978-0-7695-3121-2
DOI :
10.1109/DCC.2008.89