{"title":"Signal identification in cognitive radios using machine learning","authors":"Jingwen Zhang, Fanggang Wang","doi":"10.1049/PBTE081E_CH5","DOIUrl":null,"url":null,"abstract":"As an intelligent radio, cognitive radio (CR) allows the CR users to access and share the licensed spectrum. Being a typical noncooperative system, the applications of signal identification in CRs have emerged. This chapter introduces several signal identification techniques, which are implemented based on the machine-learning theory.","PeriodicalId":358911,"journal":{"name":"Applications of Machine Learning in Wireless Communications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applications of Machine Learning in Wireless Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/PBTE081E_CH5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
As an intelligent radio, cognitive radio (CR) allows the CR users to access and share the licensed spectrum. Being a typical noncooperative system, the applications of signal identification in CRs have emerged. This chapter introduces several signal identification techniques, which are implemented based on the machine-learning theory.
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