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IoT as a Service. 5th EAI International Conference, IoTaaS 2019, Xi’an, China, November 16-17, 2019, Proceedings

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
Zhaotun Feng1,*, Bowei Shan1,*, Yong Fang1,*
  • 1: Chang’an University
*Contact email: 2018124076@chd.edu.cn, bwshan@chd.edu.cn, fy@chd.edu.cn

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.

Keywords
UW-SWBP LDPC Overall belief
Published
2020-06-05
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-44751-9_49
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