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Open AccessArticle

Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles

1
School of Electronics and Information Engineering, Beihang University, Beijing 100083, China
2
Unmanned Systems Research Institute, Beihang University, Beijing 100083, China
3
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China
4
School of Computing & Communications, Lancaster University, Lancaster LA1 4WA, UK
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(3), 924; https://doi.org/10.3390/s18030924
Received: 11 February 2018 / Revised: 14 March 2018 / Accepted: 15 March 2018 / Published: 20 March 2018
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
Deep learning has recently attracted much attention due to its excellent performance in processing audio, image, and video data. However, few studies are devoted to the field of automatic modulation classification (AMC). It is one of the most well-known research topics in communication signal recognition and remains challenging for traditional methods due to complex disturbance from other sources. This paper proposes a heterogeneous deep model fusion (HDMF) method to solve the problem in a unified framework. The contributions include the following: (1) a convolutional neural network (CNN) and long short-term memory (LSTM) are combined by two different ways without prior knowledge involved; (2) a large database, including eleven types of single-carrier modulation signals with various noises as well as a fading channel, is collected with various signal-to-noise ratios (SNRs) based on a real geographical environment; and (3) experimental results demonstrate that HDMF is very capable of coping with the AMC problem, and achieves much better performance when compared with the independent network. View Full-Text
Keywords: deep learning; automatic modulation classification; classifier fusion; convolutional neural network; long short-term memory deep learning; automatic modulation classification; classifier fusion; convolutional neural network; long short-term memory
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Zhang, D.; Ding, W.; Zhang, B.; Xie, C.; Li, H.; Liu, C.; Han, J. Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles. Sensors 2018, 18, 924.

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