Asymmetric Joint Source-Channel Coding for Correlated Sources with Blind HMM Estimation at the Receiver
© Javier Del Ser et al. 2005
Received: 25 October 2004
Published: 8 September 2005
We consider the case of two correlated sources, and . The correlation between them has memory, and it is modelled by a hidden Markov chain. The paper studies the problem of reliable communication of the information sent by the source over an additive white Gaussian noise (AWGN) channel when the output of the other source is available as side information at the receiver. We assume that the receiver has no a priori knowledge of the correlation statistics between the sources. In particular, we propose the use of a turbo code for joint source-channel coding of the source . The joint decoder uses an iterative scheme where the unknown parameters of the correlation model are estimated jointly within the decoding process. It is shown that reliable communication is possible at signal-to-noise ratios close to the theoretical limits set by the combination of Shannon and Slepian-Wolf theorems.
Keywordsdistributed source coding hidden Markov model parameter estimation Slepian-Wolf theorem joint source-channel coding
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