Abstract With the explosive growth of vehicle applications, vehicular networks based on millimeter wave (mmWave) bands have attracted interests from both academia and industry. mmWave communications are able to utilize the huge available bandwidth to provide multiple Gbps transmission rates among vehicles. In this paper, we address the content distribution scheduling problem in mmWave vehicular networks. It has been challenging for all vehicles in the same network to complete content downloading due to the limited communication resources of roadside units (RSUs) and the high mobility of vehicles. We propose a joint vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) scheduling scheme to minimize the total number of content distribution time slots from a global optimization perspective. In the V2I phase, the RSU serially transmits integrity content to vehicles, which are selected according to the vehicular network topology and transmission scheduling scheme. In the V2V phase, full-duplex communications and concurrent transmissions are exploited to achieve content sharing between vehicles and improve transmission efficiency. Performance evaluations demonstrate that our proposed scheme reduces the number of time slots and significantly improves system throughput when compared with other schemes, especially under large-size file transfers and a large number of vehicles.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Content distribution based on joint V2I and V2V scheduling in mmWave vehicular networks


    Beteiligte:
    Su, L. (Lan) (Autor:in) / Niu, Y. (Yong) (Autor:in) / Han, Z. (Zhu) (Autor:in) / Ai, B. (Bo) (Autor:in) / He, R. (Ruisi) (Autor:in) / Wang, Y. (Yibing) (Autor:in) / Wang, N. (Ning) (Autor:in) / Su, X. (Xiang) (Autor:in)

    Erscheinungsdatum :

    2022-01-01


    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



    Mmwave Beam Management in Urban Vehicular Networks

    Zana Limani Fazliu / Francesco Malandrino / Carla Fabiana Chiasserini et al. | BASE | 2021

    Freier Zugriff

    mmWave massive MIMO vehicular communications

    Cheng, Xiang / Gao, Shijian / Yang, Liuqing | TIBKAT | 2023


    MmWave Vehicular Beam Alignment Leveraging Online Learning

    Xian, Qingyang / Doufexi, Angela / Armour, Simon | IEEE | 2023


    Modeling and Analysis of Edge Caching for 6G mmWave Vehicular Networks

    Lin, Zhijian / Fang, Yi / Chen, Pingping et al. | IEEE | 2023


    Comparing mmWave Channel Simulators in Vehicular Environments

    Lubke, Maximilian / Dimce, Sigrid / Schettler, Max et al. | IEEE | 2021