A Multi-Modal Simulation Framework to Enable Digital Twin-based V2X Communications in Dynamic Environments
This work addresses the problem of improving V2X communication reliability in high-mobility vehicular scenarios for autonomous driving and smart infrastructure, representing an incremental advancement in simulation tools.
The paper tackles the challenge of creating realistic Digital Twins for V2X communications in dynamic environments by proposing a data-driven workflow and multi-modal simulation framework, which enables accurate sensor data and mmWave/sub-THz channel modeling for tasks like blockage handover.
Digital Twins (DTs) for physical wireless environments have been recently proposed as accurate virtual representations of the propagation environment that can enable multi-layer decisions at the physical communication equipment. At high-frequency bands, DTs can help to overcome the challenges emerging in high mobility conditions featuring vehicular environments. In this paper, we propose a novel data-driven workflow for the creation of the DT of a Vehicle-to-Everything (V2X) communication scenario and a multi-modal simulation framework for the generation of realistic sensor data and accurate mmWave/sub-THz wireless channels. The proposed method leverages an automotive simulation and testing framework and an accurate ray-tracing channel simulator. Simulations over an urban scenario show the achievable realistic sensor and channel modelling both at the infrastructure and at ego-vehicles. We showcase the proposed framework on the DT-aided blockage handover task for V2X link restoration, leveraging the framework's dynamic channel generation capabilities for realistic vehicular blockage simulation.