Gated Recurrent Unit Neural Networks for Automatic Modulation Classification With Resource-Constrained End-Devices

Gated Recurrent Unit Neural Networks for Automatic Modulation Classification With Resource-Constrained End-Devices

The continuous increase in the number of mobile and Internet of Things (IoT) devices, as well as in the wireless data traffic they generate, represents an essential challenge in terms of spectral coexistence. As a result, these devices are now expected to make efficient and dynamic use of the spectr...

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Bibliographic Details
Main Authors: Ramiro Utrilla, Erika Fonseca, Alvaro Araujo, Luiz A. Dasilva
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Cognitive radio
spectrum sensing
deep learning
automatic modulation classification
recurrent neural network
gated recurrent unit
Online Access:https://ieeexplore.ieee.org/document/9118900/

Internet

https://ieeexplore.ieee.org/document/9118900/

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