University of Oulu

N. Vaara, P. Sangi, J. Pyhtilä, M. Juntti and J. Heikkilä, "A Refined Path Generation Pipeline for Radio Channel Propagation Modeling," 2023 17th European Conference on Antennas and Propagation (EuCAP), Florence, Italy, 2023, pp. 1-5, doi: 10.23919/EuCAP57121.2023.10133739.

A refined path generation pipeline for radio channel propagation modeling

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Author: Vaara, Niklas1; Sangi, Pekka1; Pyhtilä, Juha2;
Organizations: 1Center for Machine Vision and Signal Analysis
2Centre for Wireless Communcations - Radio Technologies Faculty of Information Technology and Electrical Engineering, University of Oulu Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.3 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2023
Publish Date: 2023-09-11


Ray tracing is a widely used approach for deterministic modelling of radio channels. We present our path generation pipeline, which combines environment discretization-based propagation path search with path refinement, which outputs validated paths fulfilling the Fermat’s principle of the least time. We propose a novel gradient descent-based solution for refinement. Whole pipeline is implemented as GPU computations using NVIDIA CUDA and OptiX ray tracing engine, and experimental results show efficacy of the approach.

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ISBN Print: 978-1-6654-7541-9
DOI: 10.23919/EuCAP57121.2023.10133739
Host publication: 2023 17th European Conference on Antennas and Propagation (EuCAP)
Conference: European Conference on Antennas and Propagation
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work was supported by the Ho2020 Project ARIADNE (GA 871464), Celtic Project AI4Green, and Academy of Finland 6G Flagship (Grant 346208).
EU Grant Number: (871464) ARIADNE - Artificial Intelligence Aided D-band Network for 5G Long Term Evolution
Academy of Finland Grant Number: 346208
Detailed Information: 346208 (Academy of Finland Funding decision)
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