Research Article
Signal Modulation Recognition Method based on Time-frequency Image
@INPROCEEDINGS{10.4108/eai.27-8-2020.2294229, author={Yuqian Li and Cheng Chang and Chengzhuo Shi and Sen Wang}, title={Signal Modulation Recognition Method based on Time-frequency Image}, proceedings={Proceedings of the 13th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2020, 27-28 August 2020, Cyberspace}, publisher={EAI}, proceedings_a={MOBIMEDIA}, year={2020}, month={11}, keywords={modulation recognition time-frequency cnn image processing}, doi={10.4108/eai.27-8-2020.2294229} }- Yuqian Li
Cheng Chang
Chengzhuo Shi
Sen Wang
Year: 2020
Signal Modulation Recognition Method based on Time-frequency Image
MOBIMEDIA
EAI
DOI: 10.4108/eai.27-8-2020.2294229
Abstract
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.
