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    Analysis of fluctuations of antenna pattern in U-V2X communications

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    Date
    2023-06-30
    Author
    Mohammad, Arif
    Hasna, Mazen O.
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    Abstract
    The third-generation partnership project (3GPP) defined several scenarios of vehicle-to-everything (V2X) networks such as vehicle-to-vehicle, vehicle-to-pedestrian, and vehicle-to-infrastructure. Unmanned aerial vehicles (UAVs) exploiting such scenarios for vehicular applications like vehicular-platooning, autonomous driving, and traffic management have shown improved networks’ performance in UAV-V2X (U-V2X) communications. This promising performance is typically obtained by considering high directional UAV antennas. However, the UAV vibration makes UAV antennas’ beam-width sensitive to UAV fluctuations which results in degrading the networks’ performance. Thus, in this paper, the performance of a U-V2X network in the presence of UAV fluctuations is investigated. The UAVs are modeled using an independent homogeneous Poisson Point Process and the vehicular-nodes are modeled using an independent Poisson Line Process. To this end, the association probability and success probability of various links such as vehicular-node connected to a UAV link, vehicular-node connected to a near-by vehicular-node link, and the overall U-V2X link are derived. In addition, the effect of different network settings such as the number of vehicular-nodes, UAVs, roads, and antennas is quantified. Moreover, the spectral efficiency of a U-V2X network is evaluated. Extensive simulations revealed that V2X networks facilitate UAVs and that for less dense areas with fewer roads, buildings, and crowds; UAVs provide more reliable links for connectivity than vehicular-nodes. Furthermore, it is also revealed that UAVs provide less reliable connection for V2X networks with larger UAV antenna fluctuations.
    URI
    https://www.sciencedirect.com/science/article/pii/S1874490723000691
    DOI/handle
    http://dx.doi.org/10.1016/j.phycom.2023.102066
    http://hdl.handle.net/10576/51253
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    • Electrical Engineering [‎2823‎ items ]

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