{"title":"基于统计矩的MPSK信号分类器","authors":"Yawpo Yang, S. Soliman","doi":"10.1109/GLOCOM.1991.188358","DOIUrl":null,"url":null,"abstract":"The authors report a novel moments-based classifier to classify MPSK (M-ary phase shift keying) signals by using the moments of the phase utilizing the exact phase distribution. When compared with a case in which the Tikhonov function is used to approximate the asymptotic distribution of the phase, the new classifier with 1024 samples offered a 2 dB improvement. The 2 dB improvement is offered when the probability of misclassification is 0.01. Furthermore, improvement in performance can be obtained by increasing the length of the observation interval.<<ETX>>","PeriodicalId":343080,"journal":{"name":"IEEE Global Telecommunications Conference GLOBECOM '91: Countdown to the New Millennium. Conference Record","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Statistical moments based classifier for MPSK signals\",\"authors\":\"Yawpo Yang, S. Soliman\",\"doi\":\"10.1109/GLOCOM.1991.188358\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors report a novel moments-based classifier to classify MPSK (M-ary phase shift keying) signals by using the moments of the phase utilizing the exact phase distribution. When compared with a case in which the Tikhonov function is used to approximate the asymptotic distribution of the phase, the new classifier with 1024 samples offered a 2 dB improvement. The 2 dB improvement is offered when the probability of misclassification is 0.01. Furthermore, improvement in performance can be obtained by increasing the length of the observation interval.<<ETX>>\",\"PeriodicalId\":343080,\"journal\":{\"name\":\"IEEE Global Telecommunications Conference GLOBECOM '91: Countdown to the New Millennium. Conference Record\",\"volume\":\"99 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Global Telecommunications Conference GLOBECOM '91: Countdown to the New Millennium. Conference Record\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GLOCOM.1991.188358\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Global Telecommunications Conference GLOBECOM '91: Countdown to the New Millennium. Conference Record","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GLOCOM.1991.188358","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical moments based classifier for MPSK signals
The authors report a novel moments-based classifier to classify MPSK (M-ary phase shift keying) signals by using the moments of the phase utilizing the exact phase distribution. When compared with a case in which the Tikhonov function is used to approximate the asymptotic distribution of the phase, the new classifier with 1024 samples offered a 2 dB improvement. The 2 dB improvement is offered when the probability of misclassification is 0.01. Furthermore, improvement in performance can be obtained by increasing the length of the observation interval.<>
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