Research on Automatic Modulation Recognition Using Vision Transformer 


Vol. 49,  No. 8, pp. 1074-1081, Aug.  2024
10.7840/kics.2024.49.7.1074


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  Abstract

Automatic Modulation Recognition (AMR) is a technology that plays a key role in wireless communication systems, contributing to improving the efficiency of data communication and enhancing the reliability and security of wireless communication systems. Recently, due to the development of deep learning technology, research using deep learning has been actively conducted in the field of AMR. In this paper, we propose an AMR technique based on the ViT (Vision Transformer) model, which has excellent time series data processing capabilities. The ViT model divides the input image into patches, which are small image units, and assigns an order to each patch, which is used as an input to the transformer encoder. By doing so, the ViT-based AMR model learns the characteristics of each modulation scheme and automatically recognizes the modulation scheme. By using the ViT-based AMR model, we were able to achieve an average classification accuracy improvement of about 2% even at low SNR.

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[IEEE Style]

M. Lee, M. Chae, W. Lim, "Research on Automatic Modulation Recognition Using Vision Transformer," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 8, pp. 1074-1081, 2024. DOI: 10.7840/kics.2024.49.7.1074.

[ACM Style]

Minju Lee, Myoungho Chae, and Wansu Lim. 2024. Research on Automatic Modulation Recognition Using Vision Transformer. The Journal of Korean Institute of Communications and Information Sciences, 49, 8, (2024), 1074-1081. DOI: 10.7840/kics.2024.49.7.1074.

[KICS Style]

Minju Lee, Myoungho Chae, Wansu Lim, "Research on Automatic Modulation Recognition Using Vision Transformer," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 8, pp. 1074-1081, 8. 2024. (https://doi.org/10.7840/kics.2024.49.7.1074)
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pISSN : 1226 - 4717
eISSN : 2287 - 3880