Unequally Weighted Sliding-Window Belief Propagation for Binary LDPC Codes

Zhaotun Feng; Bowei Shan; Yong Fang

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