Comparing differentiable and dynamic ray tracing: Introducing the multipath lifetime map

Sun, 30 Mar 2025 00:00:00 +0000

Abstract: With the increasing presence of dynamic scenarios, such as Vehicle-to-Vehicle communications, radio propagation modeling tools must adapt to the rapidly changing nature of the radio channel. Recently, both Differentiable and Dynamic Ray Tracing frameworks have emerged to address these challenges. However, there is often confusion about how these approaches differ and which one should be used in specific contexts. In this paper, we provide an overview of these two techniques and a comparative analysis against two state-of-the-art tools: 3DSCAT from UniBo and Sionna from NVIDIA. To provide a more precise characterization of the scope of these methods, we introduce a novel simulation-based metric, the Multipath Lifetime Map, which enables the evaluation of spatial and temporal coherence in radio channels only based on the geometrical description of the environment. Finally, our metrics are evaluated on a classic urban street canyon scenario, yielding similar results to those obtained from measurement campaigns.

Radio Propagation Modeling in an Urban Scenario using Generative Ray Path Sampling

Wed, 01 Jan 2025 00:00:00 +0000

Abstract: Radio propagation modeling remains essential for telecommunications research, where Ray Tracing provides a robust tool for simulating electromagnetic interactions in complex environments. In our previous work, we proposed a Machine Learning-assisted Ray Tracing pipeline that uses a generative approach to efficiently sample valid ray paths, significantly reducing computational complexity. In this paper, we extend this work by validating the proposed model through a comparative analysis of coverage maps. Specifically, we evaluate the accuracy of Machine Learning-generated ray paths by comparing the derived coverage maps with those produced by exhaustive Ray Tracing simulations. The results show that our approach could achieve significant computational savings while maintaining high fidelity to the ground truth, demonstrating its potential for scalable applications in wireless network design.

V. Degli-Esposti | Laurent Jacques

Comparing differentiable and dynamic ray tracing: Introducing the multipath lifetime map

Radio Propagation Modeling in an Urban Scenario using Generative Ray Path Sampling