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DOI: 10.14569/IJACSA.2019.0100721
PDF

New Approach of Automatic Modulation Classification based on in Phase-Quadrature Diagram Combined with Artificial Neural Network

Author 1: Jean Baptiste Bi Gouho
Author 2: Désiré Melèdje
Author 3: Boko Aka
Author 4: Michel Babri

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 7, 2019.

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Abstract: Automatic Modulation Classification (AMC) with intelligent system is an attracting area of research due to the development of SDR (Software Defined Radio). This paper proposes a new algorithm based on a combination of k-means clustering and Artificial Neural Network (ANN). We use constellation diagram I-Q (In phase, Quadrature) as basic information. K-means algorithm is used to normalize data transmitted and pollute by the Additive White Gaussian Noise (AWGN), then the new diagram obtained is considered as an image and coded in pixel before entering in MLP (Multi-Layer Perceptron) Neural Network. Simulation results show an improvement of recognition rate under low SNR (Signal Noise Rate) compare to some results obtained in the literature.

Keywords: Modulations; artificial neural network; clustering; machine learning

Jean Baptiste Bi Gouho, Désiré Melèdje, Boko Aka and Michel Babri, “New Approach of Automatic Modulation Classification based on in Phase-Quadrature Diagram Combined with Artificial Neural Network” International Journal of Advanced Computer Science and Applications(IJACSA), 10(7), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100721

@article{Gouho2019,
title = {New Approach of Automatic Modulation Classification based on in Phase-Quadrature Diagram Combined with Artificial Neural Network},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100721},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100721},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {7},
author = {Jean Baptiste Bi Gouho and Désiré Melèdje and Boko Aka and Michel Babri}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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