{"title":"Intelligent Radio: When Artificial Intelligence Meets the Radio Network","authors":"Tao Chen, Hsiao-Hwa Chen, Zheng Chang, S. Mao","doi":"10.1109/mwc.2020.9023916","DOIUrl":null,"url":null,"abstract":"The articles in this special section provide a comprehensive overview on the recent development of the intelligent radio. The advances in wireless communications have continuously been pushing the limit of radio technologies. Nowadays, radio networks can provide extremely high data rate, ultra-low latency, and high reliability to serve communication needs of sectors that could not be imagined before. However, radio technologies have become highly complex and call for new solutions. The recent advances in artificial intelligence (AI), including machine learning (ML), data mining, and big data analysis, bring significant promise for addressing hard problems in radio networks. It has been the increasing trend to move the intelligence beyond the spectrum access, which is primarily targeted by cognitive radio, to address various challenges in radio networks, including, but not limited to, channel modeling, modulation, beamforming, radio resource allocation, and network management. Radio technologies are on the way evolving to the intelligent radio, in which AI/ML frameworks and algorithms are applied to learn from environments and explore hidden characteristics of networks for new capacity, performance, and services. We believe the intelligent radio will be the prominent feature of next generation wireless networks. It calls for interdisciplinary research to integrate the advances in AI/ML, communications, computing, and cloud technologies. Both theoretical and applied breakthroughs are expected in this new area.","PeriodicalId":13497,"journal":{"name":"IEEE Wirel. Commun.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Wirel. Commun.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/mwc.2020.9023916","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
The articles in this special section provide a comprehensive overview on the recent development of the intelligent radio. The advances in wireless communications have continuously been pushing the limit of radio technologies. Nowadays, radio networks can provide extremely high data rate, ultra-low latency, and high reliability to serve communication needs of sectors that could not be imagined before. However, radio technologies have become highly complex and call for new solutions. The recent advances in artificial intelligence (AI), including machine learning (ML), data mining, and big data analysis, bring significant promise for addressing hard problems in radio networks. It has been the increasing trend to move the intelligence beyond the spectrum access, which is primarily targeted by cognitive radio, to address various challenges in radio networks, including, but not limited to, channel modeling, modulation, beamforming, radio resource allocation, and network management. Radio technologies are on the way evolving to the intelligent radio, in which AI/ML frameworks and algorithms are applied to learn from environments and explore hidden characteristics of networks for new capacity, performance, and services. We believe the intelligent radio will be the prominent feature of next generation wireless networks. It calls for interdisciplinary research to integrate the advances in AI/ML, communications, computing, and cloud technologies. Both theoretical and applied breakthroughs are expected in this new area.