Robust Automatic Modulation Classification Under Varying Noise Conditions

Robust Automatic Modulation Classification Under Varying Noise Conditions

Automatic modulation classification (AMC) plays a key role in non-cooperative communication systems. Feature-based (FB) methods have been widely studied in particular. Most existing FB methods are deployed at a fixed SNR level, and the pre-trained classifiers may no longer be effective when the SNR...

Full description

Bibliographic Details
Main Authors: Zhilu Wu, Siyang Zhou, Zhendong Yin, Bo Ma, Zhutian Yang
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Automatic modulation classification
feature extraction
feature selection
noise robustness
Online Access:https://ieeexplore.ieee.org/document/8017570/

Internet

https://ieeexplore.ieee.org/document/8017570/

Similar Items