Radio Modulation Classification Optimization Using Combinatorial Deep Learning Technique

Radio Modulation Classification Optimization Using Combinatorial Deep Learning Technique

We present an automatic signal modulation classification model using combinatorial deep learning technique. Our proposed deep learning model increase accuracy for low Signal-to-Noise Ratio (SNR) and maintain a high classification accuracy for high SNR signals. Using a hybrid deep learning model comb...

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Bibliographic Details
Main Authors: Ziad Elkhatib, Firuz Kamalov, Sherif Moussa, Adel Ben Mnaouer, Mustapha C.E. Yagoub, Halim Yanikomeroglu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Automatic modulation classification
dynamic spectrum allocation
deep learning techniques
transformer-block ConvLSTM
feature-based extraction
AI-based wireless communications
Online Access:https://ieeexplore.ieee.org/document/10412062/

Internet

https://ieeexplore.ieee.org/document/10412062/

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