The millimeter wave (mmWave) device-to-device air interface not only supports a direct wireless connectivity among devices, but it also offers an improved beamforming capability to obtain the direction information among the vehicles and devices for positioning. Both features serve as the key physical layer components for communications and positioning in the industrial Internet of things (IIoT) systems. Exploiting both accurate beamforming and wide bandwidth in a mmWave network, high-accuracy positioning is achievable, which can be then facilitated for location-aware communications, for instance. However, the uncertainty of anchors’ locations in the industrial environment highly degrades the achievable positioning accuracy if left without proper consideration. In order to resolve such challenge, this paper presents a cooperative positioning system (CPS), where the locations of all the vehicles and anchors can be jointly estimated based on acquired location-related measurements (LRMs). Furthermore, the positioning performance is evaluated under random trajectories and different geometric relationships between the vehicles and the anchors. We show that, the proposed positioning solution is capable of resolving the aforementioned challenge by simultaneously tracking the mobile vehicles while mapping the locations of the static anchors. Utilizing the LRMs from both time and angular domains, the achieved positioning accuracy in both 2D and vertical plane is demonstrated based on extensive numerical simulations. Last but not least, the impact of different numbers of the mobile vehicles on the overall positioning performance is also investigated.


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    Titel :

    Cooperative Positioning System for Industrial IoT via mmWave Device-to-Device Communications


    Beteiligte:
    Lu, Yi (Autor:in) / Koivisto, Mike (Autor:in) / Talvitie, Jukka (Autor:in) / Rastorgueva-Foi, Elizaveta (Autor:in) / Valkama, Mikko (Autor:in) / Simona Lohan, Elena (Autor:in)


    Erscheinungsdatum :

    01.04.2021


    Format / Umfang :

    3674930 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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