Sub-field · 9 papers
Differentiable Ray Tracing Wireless Propagation
Radio propagation modeling and wireless channel representation form the core focus, with researchers applying ray tracing, neural radiance fields (NeRF), and differentiable simulation to accurately characterize electromagnetic environments. Methods range from physics-based ray launching and differentiable ray tracers (Sionna RT, SANDWICH) to neural approaches (NeRF2, Radio Radiance Field) that learn spatial channel representations from data. Applications span indoor site-specific modeling, digital twin construction (Boston Twin), cell-free 6G network planning, and large-scale deployment of location-aware wireless systems.
Papers in this community
- Sionna RT: Differentiable Ray Tracing for Radio Propagation Modeling 2023 DOI ↗
- NeRF2: Neural Radio-Frequency Radiance Fields 2023 DOI ↗
- WiSegRT: Dataset for Site-Specific Indoor Radio Propagation Modeling with 3D Segmentation and Differentiable Ray-Tracing: (Invited Paper) 2024 DOI ↗
- Towards Practical Cell-Free 6G Network Deployments: An Open-Source End-to-End Ray Tracing Simulator 2023 DOI ↗
- SANDWICH: Towards an Offline, Differentiable, Fully-Trainable Wireless Neural Ray-Tracing Surrogate 2025 DOI ↗
- On the Digitization of the EM Environment: A Comparison of Ray Launching Solutions 2024 DOI ↗
- Boston Twin 2024 DOI ↗
- Radio Radiance Field: The New Frontier of Spatial Wireless Channel Representation 2026 DOI ↗
- Nationwide deployment and operation of a virtual arrival detection system in the wild 2021 DOI ↗