Content Delivery in Vehicular Digital Twin Using Heterogeneous Networks

Vehicular digital twins (DTs) create virtual representations of physical vehicles, enabling real-time data exchange to enhance intelligence and ensure safe driving. Reducing DT content delivery latency in infrastructure-deficient, sparsely populated areas is crucial. This paper develops a novel Satellite-UAV multi-path content delivery framework for data synchronization in vehicular DT applications. Satellites offer wide coverage but suffer from high latency, while UAVs provide rapid deployment and low-latency communication. The framework leverages these unique characteristics to facilitate simultaneous content downloading through multiple paths, thereby reducing latency. A Stackelberg game model is used to motivate effective resource allocation by UAVs. Given the typically private utility model of DTs, a learning-based algorithm is developed to determine optimal pricing strategies for UAVs. Simulation results demonstrate significant enhancements in UAV utility and reduced DT costs, meeting diverse service requirements.