Robust Computationally-Efficient Wireless Emitter Classification Using Autoencoders and Convolutional Neural Networks

Robust Computationally-Efficient Wireless Emitter Classification Using Autoencoders and Convolutional Neural Networks

This paper proposes a novel Deep Learning (DL)-based approach for classifying the radio-access technology (RAT) of wireless emitters. The approach improves computational efficiency and accuracy under harsh channel conditions with respect to existing approaches. Intelligent spectrum monitoring is a c...

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Bibliographic Details
Main Authors: Ebtesam Almazrouei, Gabriele Gianini, Nawaf Almoosa, Ernesto Damiani
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Sensors
Subjects:
Deep Learning
Denoising Autoencoders
convolutional neural networks
classification
IEEE Wi-Fi protocols
LTE
Online Access:https://www.mdpi.com/1424-8220/21/7/2414

Internet

https://www.mdpi.com/1424-8220/21/7/2414

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