Asymmetric Joint Source-Channel Coding for Correlated Sources with Blind HMM Estimation at the Receiver | Zendy

Javier Del Ser | Zendy; Pedro M. Crespo | Zendy; Olaia Galdos | Zendy

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Asymmetric Joint Source-Channel Coding for Correlated Sources with Blind HMM Estimation at the Receiver

Author(s) -

Javier Del Ser,

Pedro M. Crespo,

Olaia Galdos

Publication year - 2005

Publication title -

eurasip journal on wireless communications and networking

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.461

H-Index - 64

eISSN - 1687-1499

pISSN - 1687-1472

DOI - 10.1155/wcn.2005.483

Subject(s) - computer science , additive white gaussian noise , algorithm , decoding methods , source code , turbo code , channel (broadcasting) , a priori and a posteriori , joint (building) , markov chain , speech recognition , pattern recognition (psychology) , theoretical computer science , artificial intelligence , telecommunications , machine learning , architectural engineering , philosophy , epistemology , engineering , operating system

We consider the case of two correlated sources, $S_{1}$ and $S_{2}$ . 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 $S_{1}$ over an additive white Gaussian noise (AWGN) channel when the output of the other source $S_{2}$ 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 $S_{1}$ . 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.