{"title":"机器学习在非线性频分复用光纤通信系统中的应用","authors":"Lixia Xi, Jiacheng Wei, Wenbo Zhang","doi":"10.1109/icicn52636.2021.9673978","DOIUrl":null,"url":null,"abstract":"Nonlinear frequency division multiplexing system becomes one of the promising candidates for overcoming the fiber’s nonlinearity limitations. To improve the system’s performance, machine learning was introduced to the NFDM systems in the past few years. In this paper, an overview on the applications of machine learning in the NFDM systems is presented.","PeriodicalId":231379,"journal":{"name":"2021 IEEE 9th International Conference on Information, Communication and Networks (ICICN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Applications of Machine Learning on Nonlinear Frequency Division Multiplexing Optic-Fiber Communication Systems\",\"authors\":\"Lixia Xi, Jiacheng Wei, Wenbo Zhang\",\"doi\":\"10.1109/icicn52636.2021.9673978\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nonlinear frequency division multiplexing system becomes one of the promising candidates for overcoming the fiber’s nonlinearity limitations. To improve the system’s performance, machine learning was introduced to the NFDM systems in the past few years. In this paper, an overview on the applications of machine learning in the NFDM systems is presented.\",\"PeriodicalId\":231379,\"journal\":{\"name\":\"2021 IEEE 9th International Conference on Information, Communication and Networks (ICICN)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 9th International Conference on Information, Communication and Networks (ICICN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icicn52636.2021.9673978\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 9th International Conference on Information, Communication and Networks (ICICN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icicn52636.2021.9673978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Applications of Machine Learning on Nonlinear Frequency Division Multiplexing Optic-Fiber Communication Systems
Nonlinear frequency division multiplexing system becomes one of the promising candidates for overcoming the fiber’s nonlinearity limitations. To improve the system’s performance, machine learning was introduced to the NFDM systems in the past few years. In this paper, an overview on the applications of machine learning in the NFDM systems is presented.