Volume 37, Number 4, August 2019
|Page(s)||816 - 823|
|Published online||23 September 2019|
A Recognition Algorithm for Modulation Schemes by Convolution Neural Network and Spectrum Texture
Institute of Information and Navigation, Air Force Engineering University, Xi'an 710077, China
The recognition of modulation schemes for communication signals is an important part of communication surveillance and spectrum monitoring. An algorithm based on deep learning and spectrum texture is proposed to recognize modulation schemes. Based on imperceptible differences among various spectrums of modulation schemes, the algorithm uses Convolution Neural Network to capture the features of image texture and thus classify the features with a SOFTMAX classifier. The experiment shows the algorithm performs better than traditional algorithm based on feature parameters, while the features captured can better reveal the signal detail and reduces effort on feature parameter design.
Key words: modulation classification / spectrum texture / deep learning / convolution neural network / algorithm
关键字 : 调制识别 / 时频图纹理信息 / 深度学习 / 卷积神经网络
© 2019 Journal of Northwestern Polytechnical University. All rights reserved.
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