Vehicles are increasingly getting connected with 5G cellular connectivity, and are expected to be connected to 6G in the future. One of the key features of 5G and of 6G will be use of millimeter wave (mmW) bands. In this paper, we consider vehicles equipped with mmW connectivity. The mmW band requires beam tracking and management to achieve high data rate. This can be particularly challenging for vehicle mobility. We study how perception from cameras in a vehicle can be used to improve beam management for mmW in vehicles. We propose a reinforcement learning-based beam management technique to combine 3D maps generated from perception with current 5G beam management. Our results show that the perception can be used to significantly improve the tail of throughput. Additionally, our results show that perception can also be used to significantly reduce power needed for beam management.


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    Titel :

    Perception Assisted Millimeter Wave Beam Management for 5G/6G Connected Vehicles


    Beteiligte:
    Ashour, Mahmoud (Autor:in) / Kesavareddigari, Himaja (Autor:in) / Gulati, Kapil (Autor:in) / Cheng, Hong (Autor:in) / Marsh, Gene (Autor:in) / Patil, Shailesh (Autor:in)


    Erscheinungsdatum :

    07.10.2024


    Format / Umfang :

    3186347 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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