Research Article
Modulation Recognition Based on Neural Network Ensembles
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@INPROCEEDINGS{10.1007/978-3-030-69069-4_34, author={Xiaobo Ma and Bangnig Zhang and Daoxing Guo and Lin Cao and Guofeng Wei and Qiwei Ma}, title={Modulation Recognition Based on Neural Network Ensembles}, proceedings={Wireless and Satellite Systems. 11th EAI International Conference, WiSATS 2020, Nanjing, China, September 17-18, 2020, Proceedings, Part I}, proceedings_a={WISATS}, year={2021}, month={2}, keywords={Non-cooperative communication Modulation recognition Neural network ensembles Feature extraction}, doi={10.1007/978-3-030-69069-4_34} }- Xiaobo Ma
Bangnig Zhang
Daoxing Guo
Lin Cao
Guofeng Wei
Qiwei Ma
Year: 2021
Modulation Recognition Based on Neural Network Ensembles
WISATS
Springer
DOI: 10.1007/978-3-030-69069-4_34
Abstract
This paper studies the modulation recognition of digital communication signals based on neural networks. The BP neural network ensembles method is put forward, which is a linear composition of the BP neural networks. The recognition accuracy of ten different modulation formats is given according to the model above in feature extraction. The approach presented is superior to a neural network algorithm in existing articles. The result shows that the method proposed can recognize complex signal modulation formats availably. The overall recognition accuracy is basically up to 100% in the sample data of this paper when the SNR is more than 8 dB.
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