Research Article
Unequally Weighted Sliding-Window Belief Propagation for Binary LDPC Codes
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@INPROCEEDINGS{10.1007/978-3-030-44751-9_49, author={Zhaotun Feng and Bowei Shan and Yong Fang}, title={Unequally Weighted Sliding-Window Belief Propagation for Binary LDPC Codes}, proceedings={IoT as a Service. 5th EAI International Conference, IoTaaS 2019, Xi’an, China, November 16-17, 2019, Proceedings}, proceedings_a={IOTAAS}, year={2020}, month={6}, keywords={UW-SWBP LDPC Overall belief}, doi={10.1007/978-3-030-44751-9_49} }
- Zhaotun Feng
Bowei Shan
Yong Fang
Year: 2020
Unequally Weighted Sliding-Window Belief Propagation for Binary LDPC Codes
IOTAAS
Springer
DOI: 10.1007/978-3-030-44751-9_49
Abstract
In this paper, an Unequally Weighted Sliding-Window Belief Propagation (UW-SWBP) algorithm was proposed to decode the binary LDPC code. We model the important of overall beliefs of variable nodes in a sliding window as Gaussian distribution, which means central nodes play a more importance role than the nodes on both sides. The UW-SWBP demonstrates better performance than SWBP algorithm in both BER and FER metrics.
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