Deep Learning-Based Robust Automatic Modulation Classification for Cognitive Radio Networks

Deep Learning-Based Robust Automatic Modulation Classification for Cognitive Radio Networks

In this paper, a novel deep learning-based robust automatic modulation classification (AMC) method is proposed for cognitive radio networks. Generally, as network input of AMC convolutional neural networks (CNNs) images or complex signals are utilized in time domain or frequency domain. In terms of...

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Bibliographic Details
Main Authors: Seung-Hwan Kim, Jae-Woo Kim, Williams-Paul Nwadiugwu, Dong-Seong Kim
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Automatic modulation classification
deep learning model
convolution neural network
frame extension
cognitive radio
Online Access:https://ieeexplore.ieee.org/document/9462095/

Internet

https://ieeexplore.ieee.org/document/9462095/

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