{"title":"瑞利衰落信道中MQAM信号识别的新方法","authors":"M. Huang, Bingbing Li, B. Lan, Yanling Li","doi":"10.1109/ICCSN.2010.31","DOIUrl":null,"url":null,"abstract":"This paper presents a method for the automatic classification of MQAM signals in Rayleigh fading channel. The advantage of our method is that, by designing a feature vector which is composed of higher order moments, we do not have to acquire a priori knowledge of signal parameters, what is more, it is a simple, very low complexity, robust method. Computer simulations are made and the results show that our method can reach much better classification accuracy than the existing methods.","PeriodicalId":255246,"journal":{"name":"2010 Second International Conference on Communication Software and Networks","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A New Method for Identification of MQAM Signals in Rayleigh Fading Channel\",\"authors\":\"M. Huang, Bingbing Li, B. Lan, Yanling Li\",\"doi\":\"10.1109/ICCSN.2010.31\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a method for the automatic classification of MQAM signals in Rayleigh fading channel. The advantage of our method is that, by designing a feature vector which is composed of higher order moments, we do not have to acquire a priori knowledge of signal parameters, what is more, it is a simple, very low complexity, robust method. Computer simulations are made and the results show that our method can reach much better classification accuracy than the existing methods.\",\"PeriodicalId\":255246,\"journal\":{\"name\":\"2010 Second International Conference on Communication Software and Networks\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-02-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Conference on Communication Software and Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSN.2010.31\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Communication Software and Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSN.2010.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Method for Identification of MQAM Signals in Rayleigh Fading Channel
This paper presents a method for the automatic classification of MQAM signals in Rayleigh fading channel. The advantage of our method is that, by designing a feature vector which is composed of higher order moments, we do not have to acquire a priori knowledge of signal parameters, what is more, it is a simple, very low complexity, robust method. Computer simulations are made and the results show that our method can reach much better classification accuracy than the existing methods.
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