10 citations · 17 across the 5 of their papers we have counts for
5 papers
Transform-Invariant Generative Ray Path Sampling for Efficient Radio Propagation Modeling
Jérome Eertmans, Enrico M. Vitucci, Vittorio Degli-Esposti +3
Ray tracing has become a standard for accurate radio propagation modeling, but suffers from exponential computational complexity, as the number of candidate paths scales with the n…
Fast, Differentiable, GPU-Accelerated Ray Tracing for Multiple Diffraction and Reflection Paths
Jérome Eertmans, Sophie Lequeu, Benoît Legat +2
We present a fast, differentiable, GPU-accelerated optimization method for ray path tracing in environments containing planar reflectors and straight diffraction edges. Based on Fe…
Towards Generative Ray Path Sampling for Faster Point-to-Point Ray Tracing
Jérome Eertmans, Nicola Di Cicco, Claude Oestges +3
Radio propagation modeling is essential in telecommunication research, as radio channels result from complex interactions with environmental objects. Recently, Machine Learning has…
Comparing Differentiable and Dynamic Ray Tracing: Introducing the Multipath Lifetime Map
Jérome Eertmans, Enrico Maria Vitucci, Vittorio Degli-Esposti +2
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 radi…
Fully Differentiable Ray Tracing via Discontinuity Smoothing for Radio Network Optimization
Jerome Eertmans, Laurent Jacques, Claude Oestges
Recently, Differentiable Ray Tracing has been successfully applied in the field of wireless communications for learning radio materials or optimizing the transmitter orientation. H…