A parallel two-way split-step wavelet method for the tropospheric propagation

Thomas Bonnafont (1, 2) , Corentin Carré (1, 2) , Ali Khenchaf (1, 2)

1 Lab-STICC_PIM - Equipe PIM
2 ENSTA Bretagne - École Nationale Supérieure de Techniques Avancées Bretagne

Modeling the atmospheric long-range propagation is an important step in the development of observation, satellite, or communication systems. This paper presents a parallelized version of the two-way split-step wavelet method, designed to enhance computational efficiency. Numerical experiments in the UHF band are provided to highlight the benefits of the proposed method. In the studied cases, we observe a 25%-60% gain in terms of computation time, depending on the terrain taken into account. The proposed approach is also leveraged to generate a dataset for training a machine-learning model based on the U-Net architecture.

Mots clés: long-range propagation; split-step method; wavelet; parallel programming; machine learning

Domaines: Physique Numérique [physics.comp-ph]; Modélisation et simulation

Thomas Bonnafont, Corentin Carré, Ali Khenchaf. A parallel two-way split-step wavelet method for the tropospheric propagation. 2023 IEEE Conference on Antenna Measurements and Applications (CAMA), Nov 2023, Genoa, Italy. ⟨hal-04282130⟩