{"title":"基于机器学习算法的信道预测","authors":"Xue Jiang, Zhimeng Zhong","doi":"10.1049/PBTE081E_CH3","DOIUrl":null,"url":null,"abstract":"In this chapter, the authors address the wireless channel prediction using state-ofthe-art machine-learning techniques, which is important for wireless communication network planning and operation. Instead of the classic model-based methods, the authors provide a survey of recent advances in learning-based channel prediction algorithms. Some open problems in this field are then proposed.","PeriodicalId":358911,"journal":{"name":"Applications of Machine Learning in Wireless Communications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Channel prediction based on machine-learning algorithms\",\"authors\":\"Xue Jiang, Zhimeng Zhong\",\"doi\":\"10.1049/PBTE081E_CH3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this chapter, the authors address the wireless channel prediction using state-ofthe-art machine-learning techniques, which is important for wireless communication network planning and operation. Instead of the classic model-based methods, the authors provide a survey of recent advances in learning-based channel prediction algorithms. Some open problems in this field are then proposed.\",\"PeriodicalId\":358911,\"journal\":{\"name\":\"Applications of Machine Learning in Wireless Communications\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applications of Machine Learning in Wireless Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/PBTE081E_CH3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applications of Machine Learning in Wireless Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/PBTE081E_CH3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Channel prediction based on machine-learning algorithms
In this chapter, the authors address the wireless channel prediction using state-ofthe-art machine-learning techniques, which is important for wireless communication network planning and operation. Instead of the classic model-based methods, the authors provide a survey of recent advances in learning-based channel prediction algorithms. Some open problems in this field are then proposed.