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Symmetric Distributed Joint Source-Channel Coding Using Raptor Codes

Authors: Xuqi Zhu; Wenbo Zhang; Bin Li; Lin Zhang;

Symmetric Distributed Joint Source-Channel Coding Using Raptor Codes

Abstract

Distributed compression of correlated sources has been discussed much in wireless sensor networks, while the error-resilient implementation of this efficient coding strategy is one of the crucial issues for applications. In this paper, a symmetric Distributed Joint Source-Channel Coding (DJSCC) scheme is proposed by using Raptor codes for the independent channels case. The channel noise and the correlation of sources are considered simultaneously within one set of encoder and decoder. The symmetric structure of the proposed approach leads to more flexible and balanced rate allocation, and the rateless property of Raptor codes also guarantees tractable code rates and error correction. At last, the simulation results demonstrate that our scheme outperforms the existing LDPC-based scheme at low SNR.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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