In cellular vehicular communications, high density and mobility of vehicles require frequent resource allocation, which can cause network congestion and large signalling and processing delay. To overcome this problem, we propose a novel semi-persistent resource allocation scheme based on a two-tier heterogeneous network architecture. The architecture includes a central macro base station (MBS) and multiple roadside units (RSU). In the proposed semi-persistent scheme, the MBS pre-allocates persistent resource to RSUs based on predicted traffic, and then allocates dynamic resource upon real-time requests from RSUs while vehicles simultaneously communicate using the pre-allocated resource. A simple Space-Time k-Nearest Neighbour (ST-kNN) method is developed for short-term traffic prediction, and a geometric water-filling algorithm is developed for minimizing the relative latency. Simulation results validate the effectiveness of the proposed semi-persistent scheme in comparison with two benchmark schemes.


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    Titel :

    Semi-Persistent Resource Allocation Based on Traffic Prediction for Vehicular Communications


    Beteiligte:
    Chu, Ping (Autor:in) / Zhang, J. Andrew (Autor:in) / Wang, Xiaoxiang (Autor:in) / Fang, Gengfa (Autor:in) / Wang, Dongyu (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.06.2020


    Format / Umfang :

    1651832 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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