研究目的
To present a fully discrete Ray Launching field prediction algorithm that efficiently performs RF coverage prediction in large environments by leveraging environment visibility preprocessing and GPU parallelization.
研究成果
The RL-PPM algorithm significantly reduces computation time by three orders of magnitude compared to conventional algorithms while maintaining accuracy, making it suitable for large-scale RF coverage predictions.
研究不足
The algorithm's accuracy depends on the resolution of environment discretization and the reliability of the environment database. The preprocessing step is time-consuming but performed only once per environment.
1：Experimental Design and Method Selection:
The study employs a fully discrete Ray Launching algorithm with environment visibility preprocessing for both diffuse and specular interactions, parallelized on NVIDIA-compatible GPUs.
2：Sample Selection and Data Sources:
The algorithm is tested in urban environments with detailed 3D building databases and terrain data.
3：List of Experimental Equipment and Materials:
NVIDIA K80 GPU platform, 3D ESRI SHAPE format building-database, raster terrain-database.
4：Experimental Procedures and Operational Workflow:
The algorithm involves environment tiling, visibility preprocessing, ray launching, and bouncing rays, with computations parallelized on GPUs.
5：Data Analysis Methods:
Performance is compared to conventional ray-tracing algorithms in terms of computation time and accuracy.
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