In a dense urban area, conventional cellular V2X communications require frequent and heavy resource allocation, which can lead to processing congestion and large delay. In this paper, we propose a semi- persistent resource allocation scheme using the least minimum mean square error (LMMSE) traffic prediction in a two-tier network. The two-tier network architecture includes a central macro base station (MBS) and multiple roadside units (RSU). In the proposed scheme, the MBS pre-allocates persistent resource to RSUs based on predicted traffic, and then allocate dynamic resource upon real-time requests from vehicles through RSUs. We formulate an optimization problem for minimizing the total bandwidth under latency constraints and provide an optimal solution to the problem. Simulation is conducted for both artificially generated and real-world data, and the results validate the effectiveness of the proposed semi- persistent scheme.


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    Titel :

    Semi-Persistent V2X Resource Allocation with Traffic Prediction in Two-Tier Cellular Networks


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


    Erscheinungsdatum :

    01.04.2019


    Format / Umfang :

    1079742 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch