VoglerNet: multiple knife-edge diffraction using deep neural network - ENSTA Bretagne - École nationale supérieure de techniques avancées Bretagne Accéder directement au contenu
Communication Dans Un Congrès Année : 2020

VoglerNet: multiple knife-edge diffraction using deep neural network

Viet Dung Nguyen
Ali Mansour
Arnaud Coatanhay

Résumé

Multiple knife-edge diffraction estimation is a fundamental problem in wireless communication. One of the most well-known algorithm for predicting diffraction is Vogler algorithm which has been shown to reach the state-of-the-art results in both simulation and measurement experiments. However, it can not be easily used in practice due to its high computational complexity. In this paper, we propose VoglerNet, a data-driven diffraction estimator, by converting the Vogler algorithm into a deep neural network based system. To train VoglerNet, we propose to minimize a regularized loss function using Levenberg-Marquardt backpropagation in conjunction with a Bayesian regularization. Our numerical experiments show that VoglerNet provides fast solution in order of milliseconds while its performance is very close to that of the classical Vogler algorithm.
Fichier non déposé

Dates et versions

hal-02924177 , version 1 (27-08-2020)

Identifiants

Citer

Viet Dung Nguyen, Huy Phan, Ali Mansour, Arnaud Coatanhay. VoglerNet: multiple knife-edge diffraction using deep neural network. 2020 14th European Conference on Antennas and Propagation (EuCAP), Mar 2020, Copenhagen, France. pp.1-5, ⟨10.23919/EuCAP48036.2020.9135548⟩. ⟨hal-02924177⟩
84 Consultations
3 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More