A High-Performance GPU-Accelerated Ray-Tracing Method for Real-Time V2V Channel Modeling

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 let...

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Bibliographic Details
Published in:IEEE antennas and wireless propagation letters Vol. 24; no. 8; pp. 2527 - 2531
Main Authors: Hu, Shuo, Guo, Li-Xin, Liu, Zhongyu, Zhong, Zhigang, Nan, Zuoyong
Format: Journal Article
Language:English
Published: New York IEEE 01.08.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Accuracy
Algorithms
Bouncing
Computing time
Diffraction
Graphics processing units
Graphics processing units (GPUs)
Heuristic algorithms
high-performance computing
Modelling
Parallel processing
parallelization
Performance evaluation
Prediction algorithms
propagation
Ray tracing
ray-tracing (RT)
Real time
Receivers
Reflection
shooting and bouncing rays (SBR)
Urban environments
Vehicle dynamics
X3D
ISSN:1536-1225, 1548-5757
Online Access:Get full text
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Summary: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 graphics processing unit-parallel dynamic shooting and bouncing RT (DSRT) method that combines the advantages of shooting and bouncing ray and RT approaches. The method employs an improved adaptive ray-tube splitting mechanism to improve accuracy. A level of detail based dynamic scene update method further optimizes performance, while OptiX and compute unified device architecture (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.
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ISSN:1536-1225
1548-5757
DOI:10.1109/LAWP.2025.3567499