{"title":"基于混合信号特征的数字调制识别方法","authors":"Yangqiang Yang, Lifen Yang, Mingbo Hu","doi":"10.1109/EEI48997.2019.00050","DOIUrl":null,"url":null,"abstract":"Digital modulation recognition is an important part of signal processing. With inherent anti-noise performance, High-Order Cumulants have natural advantage in recognizing digital modulation pattern, and is widely studied in the past several decades. On the basis of high-order cumulants, combined with peak feature of FFT spectrum and instantaneous signal feature, this paper proposed a new method for digital modulation recognition based on mixed signal features, which took advantage of classical decision-tree classifier. Simulation results showed that the method proposed in this paper can recognize six classical digital modulation pattern efficiently, and achieved satisfactory recognition result even at rather low SNR.","PeriodicalId":150974,"journal":{"name":"2019 International Conference on Electronic Engineering and Informatics (EEI)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Method for Digital Modulation Recognition Based on Mixed Signal Features\",\"authors\":\"Yangqiang Yang, Lifen Yang, Mingbo Hu\",\"doi\":\"10.1109/EEI48997.2019.00050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Digital modulation recognition is an important part of signal processing. With inherent anti-noise performance, High-Order Cumulants have natural advantage in recognizing digital modulation pattern, and is widely studied in the past several decades. On the basis of high-order cumulants, combined with peak feature of FFT spectrum and instantaneous signal feature, this paper proposed a new method for digital modulation recognition based on mixed signal features, which took advantage of classical decision-tree classifier. Simulation results showed that the method proposed in this paper can recognize six classical digital modulation pattern efficiently, and achieved satisfactory recognition result even at rather low SNR.\",\"PeriodicalId\":150974,\"journal\":{\"name\":\"2019 International Conference on Electronic Engineering and Informatics (EEI)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Electronic Engineering and Informatics (EEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EEI48997.2019.00050\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Electronic Engineering and Informatics (EEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEI48997.2019.00050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Method for Digital Modulation Recognition Based on Mixed Signal Features
Digital modulation recognition is an important part of signal processing. With inherent anti-noise performance, High-Order Cumulants have natural advantage in recognizing digital modulation pattern, and is widely studied in the past several decades. On the basis of high-order cumulants, combined with peak feature of FFT spectrum and instantaneous signal feature, this paper proposed a new method for digital modulation recognition based on mixed signal features, which took advantage of classical decision-tree classifier. Simulation results showed that the method proposed in this paper can recognize six classical digital modulation pattern efficiently, and achieved satisfactory recognition result even at rather low SNR.
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