Feature Image-Based Automatic Modulation Classification Method Using CNN Algorithm

In this paper, we propose a feature image-based automatic modulation classification (AMC) method to classify modulation type. The proposed method uses a convolutional neural network (CNN) which is one of deep learning algorithms for image classification. In order to classify the modulation type, var...

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Published in:2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) pp. 1 - 4
Main Authors: Lee, Jung Ho, Kim, Kwang-Yul, Shin, Yoan
Format: Conference Proceeding
Language:English
Published: IEEE 01.02.2019
Subjects:
automatic modulation classification
Classification algorithms
convolutional neural network
Convolutional neural networks
cumulant
Deep learning
Feature extraction
Modulation
Signal to noise ratio
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Abstract In this paper, we propose a feature image-based automatic modulation classification (AMC) method to classify modulation type. The proposed method uses a convolutional neural network (CNN) which is one of deep learning algorithms for image classification. In order to classify the modulation type, various features are transformed in a two-dimensional image and this image is used as the input of the CNN. From the simulation results, we show that the proposed method improves classification performance.
AbstractList In this paper, we propose a feature image-based automatic modulation classification (AMC) method to classify modulation type. The proposed method uses a convolutional neural network (CNN) which is one of deep learning algorithms for image classification. In order to classify the modulation type, various features are transformed in a two-dimensional image and this image is used as the input of the CNN. From the simulation results, we show that the proposed method improves classification performance.
Author Lee, Jung Ho
Kim, Kwang-Yul
Shin, Yoan
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  givenname: Jung Ho
  surname: Lee
  fullname: Lee, Jung Ho
  organization: School of Electronic Engineering, Soongsil University, Seoul, 06978, Korea
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  givenname: Kwang-Yul
  surname: Kim
  fullname: Kim, Kwang-Yul
  organization: School of Electronic Engineering, Soongsil University, Seoul, 06978, Korea
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  givenname: Yoan
  surname: Shin
  fullname: Shin, Yoan
  organization: School of Electronic Engineering, Soongsil University, Seoul, 06978, Korea
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Snippet In this paper, we propose a feature image-based automatic modulation classification (AMC) method to classify modulation type. The proposed method uses a...
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SubjectTerms automatic modulation classification
Classification algorithms
convolutional neural network
Convolutional neural networks
cumulant
Deep learning
Feature extraction
Modulation
Signal to noise ratio
Title Feature Image-Based Automatic Modulation Classification Method Using CNN Algorithm
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