Channel Noise Estimation Using Particle based Belief Propagation for LDPC decoding in AWGN and BSC
Channel Noise Estimation or correlation estimation for distributed source coding Using Particle based Belief Propagation for LDPC decoding in AWGN and BSC models.
This code is partially based on our published journal papers with some additional improvements. In this code, we removed the parameter \lambda to reduce the number of free parameters. PBP estimator is distributed in the hope that is will be useful, but without any warranty. The codes have not been optimized, so the estimation speed may be slow. To use PBP estimator source code in your research, please cite our journal papers published in IEEE TCOM.
L. Cui, S. Wang, S. Cheng, M. Yeary, "Adaptive Binary Slepian-Wolf Decoding using Particle Based Belief Propagation", Communications, IEEE Transactions on 59 (9), 2337-2342, September 2011.
S. Wang, L. Cui, S. Cheng, Y. Zhai, M. Yeary, Q. Wu, "Noise Adaptive LDPC Decoding Using Particle Filtering," Communications, IEEE Transactions on, 59 (4). 913 - 916, April 2011.
Cite As
Shuang Wang (2024). Channel Noise Estimation Using Particle based Belief Propagation for LDPC decoding in AWGN and BSC (https://www.mathworks.com/matlabcentral/fileexchange/39725-channel-noise-estimation-using-particle-based-belief-propagation-for-ldpc-decoding-in-awgn-and-bsc), MATLAB Central File Exchange. Retrieved .
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JavaPBPForMatlab/Utils/
Version | Published | Release Notes | |
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1.0.0.0 |