Year: 2025
Type: article
Abstract: Vehicle-to-vehicle (V2V) communications require highly accurate and real-time channel modeling techniques. The dynamic nature of V2V scenarios demands continuous scene updates while ray-tracing (RT) algorithms typically require substantial computational time to achieve accurate predictions. This letter proposes an OptiX-based GPU-parallel dynamic shooting and bouncing ray tracing (DSRT) method that combines the advantages of shooting and bouncing ray (SBR) and RT approaches. The method employs an improved adaptive ray-tube splitting mechanism to improve accuracy. A level of detail (LOD)-based dynamic scene update method further optimizes performance, while OptiX and CUDA acceleration enable efficient RT. Channel measurements in urban environments demonstrate the high accuracy of our algorithm. Performance evaluation results show that DSRT achieves a parallelization degree exceeding 98.8% and delivers exceptional speedup ratios.
Authors: Shuo Hu, Li-Xin Guo, Zhongyu Liu, Zhigang Zhong, Zuoyong Nan
Institution: Xidian University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,645
OpenAlex ID: W4410114786