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Self-Corrected Belief-Propagation Decoder for Source Coding With Unknown Source Statistics
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DOI：10.1109/LCOMM.2021.3075110.png)
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摘要
En 中文
This letter describes a practical Slepian-Wolf source coding scheme based on Low Density Parity Check (LDPC) codes. It considers the realistic setup where the parameters of the statistical model between the source and the side information are unknown. A novel Self-Corrected Belief-Propagation (SC-BP) algorithm is proposed in order to make the coding scheme robust to incorrect model parameters by introducing some memory inside the LDPC decoder. A Two Dimensional Density Evolution (2D-DE) analysis is then developed to predict the theoretical performance of the SC-BP decoder. Both the 2D-DE analysis and Monte-Carlo simulations confirm the robustness of the SC-BP decoder. The proposed solution allows for an important complexity reduction and shows a performance very close to existing methods which jointly estimate the model parameters and the source sequence.
Keyword:
Decoding
Parity check codes
Source coding
Probability distribution
Standards
Robustness
Signal to noise ratio
Slepian-Wolf source coding
LDPC codes
density evolution
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IF:
4.4
论文数:
1.3W
被引数:
2.2W
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