5G for Future Wireless Networks. First International Conference, 5GWN 2017, Beijing, China, April 21-23, 2017, Proceedings

Research Article

Big Data-Driven Vehicle Mobility Analysis and Design for 5G

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  • @INPROCEEDINGS{10.1007/978-3-319-72823-0_23,
        author={Ruoxi Sun and Kai Zhang and Yong Ren},
        title={Big Data-Driven Vehicle Mobility Analysis and Design for 5G},
        proceedings={5G for Future Wireless Networks. First International Conference, 5GWN 2017, Beijing, China, April 21-23, 2017, Proceedings},
        proceedings_a={5GWN},
        year={2018},
        month={1},
        keywords={Big data Vehicle mobility 5G},
        doi={10.1007/978-3-319-72823-0_23}
    }
    
  • Ruoxi Sun
    Kai Zhang
    Yong Ren
    Year: 2018
    Big Data-Driven Vehicle Mobility Analysis and Design for 5G
    5GWN
    Springer
    DOI: 10.1007/978-3-319-72823-0_23
Ruoxi Sun1,*, Kai Zhang1,*, Yong Ren1,*
  • 1: Tsinghua University
*Contact email: xysrx@163.com, zhang-k16@mails.tsinghua.edu.cn, reny@tsinghua.edu.cn

Abstract

Each generation of communication technology has a subversion, 5G will have a greater bandwidth, high carrier frequency, extreme base station and device densities, especially in vehicular network. Mobility models play a pivotal role in vehicular network, especially for routing policy evaluation. Relying on big data technology, the big data aided vehicle mobility analysis and design gets a lot of attentions. In this paper, we commerce with introducing the data set, i.e., a big GPS data set in Beijing. Then, a novel vehicle and location collaborative mobility scheme is proposed relying the GPS data set. We evaluate its performance based on degree distribution, duration distribution and interval time distribution. Our works may help the mobility design in vehicular networks.