{"title":"基于深度学习的通用DPD系统","authors":"C. I, Yingchao Lin, Guizhen Wang","doi":"10.1109/IEDM13553.2020.9371952","DOIUrl":null,"url":null,"abstract":"Facing the severe power consumption and energy efficiency challenges in 5G era, a novel DPD solution enabled by deep learning and big data is proposed. This is a flexible system suitable for various wireless network architectures and diverse application scenarios. The architecture, mechanism and deployment strategy along with its advantages are presented. Preliminary validation and analyses are also illustrated for the feasibility.","PeriodicalId":415186,"journal":{"name":"2020 IEEE International Electron Devices Meeting (IEDM)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Deep Learning Enabled Universal DPD System\",\"authors\":\"C. I, Yingchao Lin, Guizhen Wang\",\"doi\":\"10.1109/IEDM13553.2020.9371952\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Facing the severe power consumption and energy efficiency challenges in 5G era, a novel DPD solution enabled by deep learning and big data is proposed. This is a flexible system suitable for various wireless network architectures and diverse application scenarios. The architecture, mechanism and deployment strategy along with its advantages are presented. Preliminary validation and analyses are also illustrated for the feasibility.\",\"PeriodicalId\":415186,\"journal\":{\"name\":\"2020 IEEE International Electron Devices Meeting (IEDM)\",\"volume\":\"57 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Electron Devices Meeting (IEDM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEDM13553.2020.9371952\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Electron Devices Meeting (IEDM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEDM13553.2020.9371952","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Facing the severe power consumption and energy efficiency challenges in 5G era, a novel DPD solution enabled by deep learning and big data is proposed. This is a flexible system suitable for various wireless network architectures and diverse application scenarios. The architecture, mechanism and deployment strategy along with its advantages are presented. Preliminary validation and analyses are also illustrated for the feasibility.
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