Vehicle Ad-hoc Network (VANET) has attracted much research in recent years; VANET is the wireless communication to the roadside infrastructure between the Vehicle to Vehicle (V2V). Software-Defined Networking (SDN) -based architecture provides flexibility, scalability, programming and global knowledge. At the same time, it can also provide delay-sensitive and location-aware services to meet the needs of the VANET. 5G provides a flexible architecture and service management for wireless communication between Vehicles to Everything (V2X); during vehicles communicate to other vehicles or external environment, it is also possible to provide VANET in a large amount of system capacity, a delay reduced, and it reduces the cost. It can meet the growth expectations of the tailor-made vehicular service. Vehicle communication has traffic safety, user application-based problems with some special design requirements that cause high mobility in a vehicle, and 5G spectral heterogeneity has been a challenge to realize the dynamic spectrum sharing for better quality highly efficient VANET. To provide effective 5G enabled VANET here three methods are proposed named Cellular Base station using SDN, VANET mobility model, and multi-mode spectrum sharing in 5G VANET with an efficient algorithm of Dynamic Short Range Mobility Patterns based Vehicular Communications (DSRMPVC) thus, using the above methods and algorithms, it used to solve critical challenges between the Vehicle to Vehicle (V2V), Vehicle to Infrastructure (V2I), and Vehicle to Base station (V2B) to improve the communication of the vehicle. It can respond quickly to solve the serious challenges of VANET, road conditions, traffic, accidents, and it is used to reduce energy consumption and vehicle emissions. Simulation results: The proposed methods and algorithms describe superiority over existing methods, particularly for roadside units with large noise variance


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    Titel :

    Dynamic Short Range Mobility Patterns based Vehicular Communications for 5G-VANET


    Beteiligte:
    Ali, Shoukath (Autor:in) / Baba, Khadar (Autor:in) / P, Sandeep (Autor:in) / L, Prakash B. (Autor:in)


    Erscheinungsdatum :

    29.04.2023


    Format / Umfang :

    1039413 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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