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VoglerNet: multiple knife-edge diffraction using deep neural network

Nguyen, Viet Dung and Phan, Huy and Mansour, Ali and Coatanhay, Arnaud (2020) VoglerNet: multiple knife-edge diffraction using deep neural network. In: 2020 14th European Conference on Antennas and Propagation (EuCAP), 15-20 March 2020, Copenhagen, Denmark,.

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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.

Item Type: Conference or Workshop Item (Paper)
Subjects: Electronics and Communications > Communications
Divisions: Advanced Insitute of Engineering and Technology (AVITECH)
Depositing User: Lê Trung Thành
Date Deposited: 17 Dec 2020 05:22
Last Modified: 17 Dec 2020 05:22

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