Deep Learning-Based Automatic Modulation Classification Using Robust CNN Architecture for Cognitive Radio Network

Faculty Engineering Year: 2023
Type of Publication: ZU Hosted Pages:
Authors:
Ola Fekry Abdelaziz Abdelaziem
Journal: sensors MDPI Volume:
Keywords : Deep Learning-Based Automatic Modulation Classification Using    
Abstract:
This article proposes a robust automatic modulation classification (AMC) model based on a new architecture of convolutional neural network (CNN). The proposed model improved the classification accuracy at very low Signal-to-Noise Ratio (SNR) and achieved near-optimal classification at high SNR. The proposed architecture has strong feature extraction abilities that can effectively recognize 16QAM and 64QAM signals, the challenging modulation schemes of the same modulation family
    
     
 
       

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