Future vehicular applications like Tele-Operated Driving (ToD) and Communication-Based Train Control (CBTC) pose demanding requirements on mobile communication networks. Despite continuous 5G technology upgrades and expansion strategies, mobile networks cannot provide a full-coverage service guarantee for the required mission-critical Key Performance Indicators (KPIs). However, application and location-specific Quality of Service (QoS) predictions are crucial to reliably meet the highest QoS compliance of emerging future smart city services.Therefore, this paper proposes a digital twin capable of merging connectivity data with arbitrary application domains to derive KPI predictions for mission-critical applications. The potential of the proposed approach is illustrated based on a case study in the urban area of Dortmund, Germany, considering data rate and latency predictions for mobile applications. In this context, a continuous data flow for the multi-dimensional mobile network twin is acquired using a massive, multimodal measurement campaign enabled by road and rail-based vehicles. This ever-growing database is utilized to analyze the KPI requirements of selected vehicular applications.For an example ToD target zone, it is shown that a multi-Mobile Network Operator (MNO) approach increases the KPI fulfillment of direct control ToD from approximately 70% to 90% compared to a single MNO. By further restricting the ToD zone and combining two MNOs, a ToD-ready zone with 100% fulfillment of the KPIs is reached.


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    Titel :

    Data-Driven Digital Mobile Network Twin Enabling Mission-Critical Vehicular Applications


    Beteiligte:


    Erscheinungsdatum :

    01.06.2023


    Format / Umfang :

    11507057 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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