Signal Modulation Recognition Method based on Time-frequency Image

Li, Yuqian and Chang, Cheng and Shi, Chengzhuo and Wang, Sen (2020) Signal Modulation Recognition Method based on Time-frequency Image. In: Mobimedia 2020, 27-28 August 2020, Cyberspace.

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Signal modulation classification is an important technology for signal processing, in order to get higher recognition accuracy at low signal-to-noise ratios, this paper proposed a modulation recognition algorithm which combines CNN and time-frequency analysis methods. The method’s steps are as following, first, make the SPWVD transforms to the digital signals to obtain corresponding time-frequency images. Then, use image processing method to enhance the obtained images, such as image gray processing, perform the grayscale equalization and binarization the images. After that, the pictures are inputted into the CNN network for classification and recognition. The experimental results show that the recognition rate can achieve 90.44% at 0dB.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: modulation recognition time-frequency cnn image processing
Subjects: T Technology > T Technology (General)
Depositing User: EAI Editor I.
Date Deposited: 04 Feb 2021 14:25
Last Modified: 04 Feb 2021 14:25

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