“radio propagation”

Abstract: Ray tracing is a widely used method to model radio wave propagation in complex environments. However, traditional ray tracing tools are often not differentiable, preventing their use in gradient-based optimization and machine learning pipelines.

Abstract: This proposal presents a demonstration of DiffeRT, an open-source Differentiable Ray Tracing toolbox designed for Machine Learning and optimization applications in the context of radio propagation. Built on the JAX framework for differentiable programming and the Equinox library as a Machine Learning framework, DiffeRT extends its predecessor, DiffeRT2d, to support 3D scenes with enhanced performance and higher-level electromagnetic field computation features.

Abstract: Ray Tracing (RT) is arguably one of the most prevalent methodologies in the field of radio propagation modeling. However, access to RT software is often constrained by its closed-source nature, licensing costs, or the requirement of high-performance computing resources.