Summary
International Conference on Emerging Technologies for Communications
2020
Session Number:B4
Session:
Number:B4-3
A study on automatic modulation classification of digital modulation signals using Convolutional Neural Network
Yutao Liu, Toru Nishiyama, Shigeru Tomisato, Kazuhiro Uehara,
pp.-
Publication Date:2020/12/2
Online ISSN:2188-5079
DOI:10.34385/proc.63.B4-3
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Summary:
Automatic Modulation Classification (AMC) of the transmitted signals remains a challenging area in modern intelligent communication systems such as cognitive radio system. There are some problems such as low efficiency and low accuracy for traditional classification systems. Therefore, we propose a new system for AMC using Convolutional Neural Network (CNN) with constellation diagrams in Additive White Gaussian Noise channel and use the trained model to achieve modulation recognition with constellation diagrams. After using new CNN models, improved input image size, number of dropout layers and simulation hyperparameters, we have achieved high efficiency and high precision recognition of modulation methods.