Lightweight Deep Learning Model for Automatic Modulation Classification in Cognitive Radio Networks

Lightweight Deep Learning Model for Automatic Modulation Classification in Cognitive Radio Networks

Automatic modulation classification (AMC) used in cognitive radio networks is an important class of methods apt to utilize spectrum resources efficiently. However, conventional likelihood-based approaches have high computational complexity. Thus, this paper proposes a novel convolutional neural netw...

Full description

Bibliographic Details
Main Authors: Seung-Hwan Kim, Jae-Woo Kim, Van-Sang Doan, Dong-Seong Kim
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Automatic modulation classification
deep learning model
convolution neural network
light weight
cognitive radio
Online Access:https://ieeexplore.ieee.org/document/9240929/

Internet

https://ieeexplore.ieee.org/document/9240929/

Similar Items