Abstract. To support vehicle to everything (V2X) communication which is an integral part of intelligent transportation systems (ITS), fifth generation (5G) communication systems will need to employ diverse range of technologies, which will ultimately lead to automated driving, improved traffic safety, improved traffic efficiency and infotainment.~V2X is considered as one of the most challenging applications of 5G, because it requires ultra reliable and low latency communication (URLLC) for safety critical applications and high data rates in many scenarios under mobility. Vehicles which can communicate with a base station or road side unit (RSU) are primary vehicles, which can act as relays to secondary vehicles which are out of coverage from the network. Therefore vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) communication are employed to provide coverage for out of coverage vehicles. In this study joint problem of admission control for primary vehicles and user association for secondary vehicles in a singe cell downlink vehicular network is considered. The objective is to maximize the number of admitted primary vehicles, while associating all secondary vehicles. We consider the underlying communication system is based on millimeter wave communication at 60 GHz and we cast the optimization problem as an ℓ₀ minimization problem. This problem is known to be combinatorial and NP-hard. Hence, we propose a sub optimal, two stage algorithm to solve it. We compare the performance of proposed algorithm against the exhaustive search algorithm. From simulation results it can be observed, although the proposed algorithm is a sub optimal algorithm it gives optimal performance with improved efficiency. Hence, the proposed algorithm is able to determine the optimal association for vehicles which are out of coverage and optimal admission for vehicles which are in coverage.


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    Title :

    Joint admission and association in vehicular networks


    Contributors:

    Publication date :

    2019-07-31


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    DDC:    629




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