In this work, non-linear supervised learning classifiers are proposed for Physical Layer Authentication (PLA). Their performance is evaluated using a Universal Software Radio Peripheral (USRP) based testbed under randomly distributed attacks and burst attacks within a mobile Ultra Reliable Low Latency Communication (URLLC) campus network scenario. It is shown, that in specific cases, non-linear classifiers can achieve promising results in terms of authentication accuracy and Receiver Operating Characteristics (ROCs) curve performance.


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    Titel :

    URLLC Physical Layer Authentication based on non-linear Supervised Learning


    Beteiligte:


    Erscheinungsdatum :

    01.06.2023


    Format / Umfang :

    1198417 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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