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

Research Article

Sliding-Window Belief Propagation with Unequal Window Size for Nonstationary Heterogeneous Source

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  • @INPROCEEDINGS{10.1007/978-3-030-44751-9_31,
        author={Jiao Fan and Bowei Shan and Yong Fang},
        title={Sliding-Window Belief Propagation with Unequal Window Size for Nonstationary Heterogeneous Source},
        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={SWBP algorithm Belief propagation LDPC code},
        doi={10.1007/978-3-030-44751-9_31}
    }
    
  • Jiao Fan
    Bowei Shan
    Yong Fang
    Year: 2020
    Sliding-Window Belief Propagation with Unequal Window Size for Nonstationary Heterogeneous Source
    IOTAAS
    Springer
    DOI: 10.1007/978-3-030-44751-9_31
Jiao Fan1,*, Bowei Shan1,*, Yong Fang1,*
  • 1: Chang’an University
*Contact email: 2018124056@chd.edu.cn, bwshan@chd.edu.cn, fy@chd.edu.cn

Abstract

This paper presents a Sliding-Window Belief Propagation with Unequal Window Size (SWBP-UWS) algorithm to deal with the nonstationary heterogeneous source. In this algorithm, the entire source is divided into several sections according to its variation and each optimum window size is individually determined by each section. The experimental results show this algorithm outperforms the SWBP algorithm.