{"title":"Machine Learning: The Panacea for 5G Complexities","authors":"N. Hari Kumar;Sandhya Baskaran","doi":"10.13052/jicts2245-800X.726","DOIUrl":null,"url":null,"abstract":"It's not a myth that transition in next generation technology brings with it a set of exciting applications as well as challenges to the telecom ecosystem and in-turn paves way for new revenue streams. 5G enables ultra-high data rates, exceptional low latencies which enables the telecom operator for the facilitation of interesting parallels like loT and Next-Gen Industrial enhance-ments like autonomous vehicles, connected mines, connected agriculture and mission critical communications by enhancing infrastructure, software and hardware components of the 5G system. As imminent new features of 5G like Multiple Input Multiple Output (MIMO), network slices, virtual network functions, indoor localization, Machine to Machine (M2M) capabilities are highly appreciated, it also opens new set of challenges like real time dynamic configurations, low latency handovers. These challenges can be addressed with the application of AI technologies to components at the crux of 5G system. Here in this paper, we discuss some of the major challenges such as data burst, improving performance, fault tolerance and traffic management with new components appended to the 5G system, required upgrades to existing technology and how Machine Learning (ML), Artificial Intelligence (AI), becomes the self-evident answer to these stumbling blocks.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"7 2","pages":"157-170"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.13052/jicts2245-800X.726","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of ICT Standardization","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10258042/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Decision Sciences","Score":null,"Total":0}
引用次数: 3
Abstract
It's not a myth that transition in next generation technology brings with it a set of exciting applications as well as challenges to the telecom ecosystem and in-turn paves way for new revenue streams. 5G enables ultra-high data rates, exceptional low latencies which enables the telecom operator for the facilitation of interesting parallels like loT and Next-Gen Industrial enhance-ments like autonomous vehicles, connected mines, connected agriculture and mission critical communications by enhancing infrastructure, software and hardware components of the 5G system. As imminent new features of 5G like Multiple Input Multiple Output (MIMO), network slices, virtual network functions, indoor localization, Machine to Machine (M2M) capabilities are highly appreciated, it also opens new set of challenges like real time dynamic configurations, low latency handovers. These challenges can be addressed with the application of AI technologies to components at the crux of 5G system. Here in this paper, we discuss some of the major challenges such as data burst, improving performance, fault tolerance and traffic management with new components appended to the 5G system, required upgrades to existing technology and how Machine Learning (ML), Artificial Intelligence (AI), becomes the self-evident answer to these stumbling blocks.