A Sampling-based Distributed Source Coding Scheme

In many practical distributed source coding (DSC) schemes that apply channel coding and iterative decoding, correlation estimation provides the likelihood information about the source bits to initialize the decoding algorithms. Therefore, the decoding depends strongly on the accuracy of this correla...

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Vydáno v:Journal of physics. Conference series Ročník 1914; číslo 1; s. 12022 - 12027
Hlavní autoři: Mo, H, Chen, J, Li, J, Zhao, M
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bristol IOP Publishing 01.05.2021
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ISSN:1742-6588, 1742-6596
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Abstract In many practical distributed source coding (DSC) schemes that apply channel coding and iterative decoding, correlation estimation provides the likelihood information about the source bits to initialize the decoding algorithms. Therefore, the decoding depends strongly on the accuracy of this correlation estimation information. In this study, a sampling-based scheme for DSC is proposed that takes advantage of the source redundancy without requiring prior knowledge of its statistics. At the sender, the source sequence is sampled to obtain the sampled and unsampled sub-sequences. Then, the un-sampled sub-sequence is compressed by an arithmetic coder. Meanwhile the syndromes of the sampled sub-sequence are also calculated. At the receiver, the correlation between the side information and the un-sampled sub-sequence is used to estimate the conditional marginal distribution of the sampled sub-sequence. Then, the estimated information is used to initialize the likelihood information of the decoding algorithms. Finally, the likelihood information is combined with the received syndromes to perform iterative decoding to recover the original sampled sub-sequence. Experiment results show that the proposed scheme achieves better rate-distortion performance compared with the existing DSC schemes.
AbstractList In many practical distributed source coding (DSC) schemes that apply channel coding and iterative decoding, correlation estimation provides the likelihood information about the source bits to initialize the decoding algorithms. Therefore, the decoding depends strongly on the accuracy of this correlation estimation information. In this study, a sampling-based scheme for DSC is proposed that takes advantage of the source redundancy without requiring prior knowledge of its statistics. At the sender, the source sequence is sampled to obtain the sampled and unsampled sub-sequences. Then, the un-sampled sub-sequence is compressed by an arithmetic coder. Meanwhile the syndromes of the sampled sub-sequence are also calculated. At the receiver, the correlation between the side information and the un-sampled sub-sequence is used to estimate the conditional marginal distribution of the sampled sub-sequence. Then, the estimated information is used to initialize the likelihood information of the decoding algorithms. Finally, the likelihood information is combined with the received syndromes to perform iterative decoding to recover the original sampled sub-sequence. Experiment results show that the proposed scheme achieves better rate-distortion performance compared with the existing DSC schemes.
Author Mo, H
Chen, J
Li, J
Zhao, M
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10.1109/TIT.2004.839518
10.1007/s11042-016-4245-x
10.1109/LCOMM.2007.071172
10.1109/TIP.2011.2175936
10.1109/TIT.1973.1055037
10.1109/TIT.2008.920187
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Snippet In many practical distributed source coding (DSC) schemes that apply channel coding and iterative decoding, correlation estimation provides the likelihood...
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SubjectTerms Algorithms
Codes
Coding
Correlation Estimation
Decoding
Disorders
Distributed Source Coding (DSC)
LDPC code
Physics
Redundancy
Sampling
Side Information
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Title A Sampling-based Distributed Source Coding Scheme
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