🤖 AI Summary
To address key challenges in V2X multi-technology (DSRC/C-V2X) spectrum coexistence simulation—including physical-layer modeling inaccuracies, bimodal SINR distortion induced by LoS/NLoS propagation conditions, and coarse-grained interference quantification—this paper proposes the first open-source, full-stack V2X digital twin framework. Methodologically, it introduces a novel “ray-tracing-in-the-loop” architecture that tightly integrates the Sionna engine to enable high-fidelity, vehicle-grid-level channel modeling—including dynamic occlusion, Doppler shifts, and diffraction/scattering effects. A cross-technology interference tracking module is designed to eliminate SINR distortion inherent in conventional LoS/NLoS classification models. Furthermore, the framework enables, for the first time, fine-grained, time-frequency resource-level interference quantification across heterogeneous V2X technologies. Experimental evaluation demonstrates over 50% and 70% reductions in application-layer communication performance error in rural and urban scenarios, respectively, significantly improving simulation accuracy and scalability.
📝 Abstract
This paper presents VaN3Twin-the first open-source, full-stack Network Digital Twin (NDT) framework for simulating the coexistence of multiple Vehicle-to-Everything (V2X) communication technologies with accurate physical-layer modeling via ray tracing. VaN3Twin extends the ms-van3t simulator by integrating Sionna Ray Tracer (RT) in the loop, enabling high-fidelity representation of wireless propagation, including diverse Line-of-Sight (LoS) conditions with focus on LoS blockage due to other vehicles' meshes, Doppler effect, and site-dependent effects-e.g., scattering and diffraction. Unlike conventional simulation tools, the proposed framework supports realistic coexistence analysis across DSRC and C-V2X technologies operating over shared spectrum. A dedicated interference tracking module captures cross-technology interference at the time-frequency resource block level and enhances signal-to-interference-plus-noise ratio (SINR) estimation by eliminating artifacts such as the bimodal behavior induced by separate LoS/NLoS propagation models. Compared to field measurements, VaN3Twin reduces application-layer disagreement by 50% in rural and over 70% in urban environments with respect to current state-of-the-art simulation tools, demonstrating its value for scalable and accurate digital twin-based V2X coexistence simulation.