Open AccessCombined hidden Markov source estimation and low‐density parity‐check coding: a novel joint source–channel coding scheme for multimedia communications
Author(s) -
Yin Liuguo,
Lu Jianhua,
Wu Youshou
Publication year - 2002
Publication title -
wireless communications and mobile computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.42
H-Index - 64
eISSN - 1530-8677
pISSN - 1530-8669
DOI - 10.1002/wcm.86
Subject(s) - computer science , low density parity check code , decoding methods , algorithm , additive white gaussian noise , theoretical computer science , channel (broadcasting) , markov chain , coding (social sciences) , computer engineering , computer network , mathematics , statistics , machine learning
Joint source–channel coding schemes have been proven to be very effective for reliable multimedia communications. In this paper, we develop a joint source–channel coding scheme that combines the hidden Markov source (HMS) estimation and the low‐density parity‐check (LDPC) codes with an iterative estimation/decoding scheme. With this innovative combination, multimedia source redundancy could be accurately extracted by the hidden Markov estimation without any a priori information about the source. Moreover, the interleaver that is usually used to separate the source coding and channel coding can be avoided by exploiting the randomizing property of the LDPC codes. Furthermore, the channel decoding procedure may be implemented in parallel, resulting in good performance with a fairly low decoding complexity and delay. Simulation results have shown that the proposed scheme can achieve much better performance than the standard coding scheme over the binary input additive white Gaussian noise (BIAWGN) channels. Copyright © 2002 John Wiley & Sons, Ltd.