Empowering Wireless Digital Twins with Ray Tracing Simulations

At the crossroad between simulation and machine learning, digital twin systems are envisioned to bridge the theoretical guarantees of model-based approaches with the flexibility of data-driven methods. However, one major concern is whether insights drawn from the simulation can still apply to the real world. Embodying both the opportunities and challenges of simulation intelligence, we believe that ray tracing will drive the understanding of signal propagation in the next generation of wireless digital twins, while relying on machine learning to cope with the diversity of real-world materials and inaccuracies in the available geometry.