Technologies for Efficient Amateur Drone Detection in 5G Millimeter-Wave Cellular Infrastructure

Dmitrii Solomitckii, Margarita Gapeyenko, Vasilii Semkin, Sergey Andreev, Yevgeni Koucheryavy

    Tutkimustuotos: ArtikkeliScientificvertaisarvioitu

    49 Sitaatiot (Scopus)
    118 Lataukset (Pure)

    Abstrakti

    Unmanned aerial vehicles, also called drones, are recently gaining increased research attention across various fields due to their flexibility and application potential. The steady increase in the number of amateur drones demands more stringent regulations on their allowed route, mass, and load. However, these regulations may be violated accidentally or deliberately. In these cases, spying with drones, transfer of dangerous payloads, or losing reliable drone control can represent a new hazard for people, governments, and business sector. The technologies to detect, track, and disarm possible aerial threats are therefore in prompt demand. To this end, ubiquitous cellular networks, and especially 5G infrastructures based on the use of millimeter-wave radio modules, may be efficiently leveraged to offer the much needed drone detection capabilities. In this work, we propose to exploit 5G millimeter-wave deployments to detect violating amateur drones. We argue that the prospective 5G infrastructure may provide all the necessary technology elements to support efficient detection of small-sized drones. We therefore outline a novel technology and system design perspective, including such considerations as the density of base stations, their directional antennas, and the available bandwidth, among others, as well as characterize their impact with our ray-based modeling methods.

    AlkuperäiskieliEnglanti
    Sivut43-50
    Sivumäärä8
    JulkaisuIEEE Communications Magazine
    Vuosikerta56
    Numero1
    DOI - pysyväislinkit
    TilaJulkaistu - 1 tammik. 2018
    OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

    Julkaisufoorumi-taso

    • Jufo-taso 2

    !!ASJC Scopus subject areas

    • Computer Science Applications
    • Computer Networks and Communications
    • Electrical and Electronic Engineering

    Sormenjälki

    Sukella tutkimusaiheisiin 'Technologies for Efficient Amateur Drone Detection in 5G Millimeter-Wave Cellular Infrastructure'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

    Siteeraa tätä