345 citations
- Carleton UniversityCA4 papers
- Memorial University of NewfoundlandCA2 papers
- Arcetri Astrophysical ObservatoryIT1 paper
- Brera Astronomical ObservatoryIT1 paper
- California Institute of TechnologyUS1 paper
- CEA CadaracheFR1 paper
- CEA GrenobleFR1 paper
- CEA Paris-SaclayFR1 paper
- Château GombertFR1 paper
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR1 paper
- Durham UniversityGB1 paper
- École Polytechnique Fédérale de LausanneCH1 paper
Showing 2024 · eess.SPShow all
3 papers · 2 filters
eess.SP2024★ 13 cited
Map-Based Path Loss Prediction in Multiple Cities Using Convolutional Neural Networks
Ryan G. Dempsey, Jonathan Ethier, Halim Yanikomeroglu
Radio deployments and spectrum planning benefit from path loss predictions. Obstructions along a communications link are often considered implicitly or through derived metrics such…
eess.SP2024★ 9 cited
Extending Machine Learning Based RF Coverage Predictions to 3D
Muyao Chen, Mathieu Châteauvert, Jonathan Ethier
This paper discusses recent advancements made in the fast prediction of signal power in mmWave communications environments. Using machine learning (ML) it is possible to train mode…
eess.SP2024★ 4 cited
Signal Attenuation through Foliage Estimator (SAFE)
Mathieu Châteauvert, Jonathan Ethier, Pierre Bouchard
The SAFE tool is an open-source Radio Frequency (RF) propagation model designed for path loss predictions in foliage-dominant environments. It utilizes the ITU-R P.1812-6 model as…