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1. 中国移动通信有限公司研究院,北京 100053
2. 维沃移动通信有限公司,广东 东莞 523000
[ "李爱华(1974- ),男,现就职于中国移动通信有限公司研究院,主要研究方向为5G-Advanced 架构演进、网络智能化、物联网技术等" ]
[ "吴晓波(1979- ),男,现就职于维沃移动通信有限公司,IMT2020(5G)推进组 5G与 AI 融合研究组副组长,主要研究方向为4G/5G语音、5G智能化等" ]
[ "陈超(1989- ),女,现就职于中国移动通信有限公司研究院,主要研究方向为5G网络智能化" ]
[ "魏彬(1983-),男,中国移动通信有限公司研究院网络与 IT 技术研究所高级工程师、副所长,主要从事3G/4G/5G核心网标准化推进及商用技术攻关、5G行业网等方面的工作" ]
[ "史嫄嫄(1984- ),女,博士,现就职于中国移动通信有限公司研究院,主要研究方向为5G网络智能化" ]
网络出版日期:2022-08,
纸质出版日期:2022-08-20
移动端阅览
李爱华, 吴晓波, 陈超, 等. 5G网络大数据智能分析技术[J]. 电信科学, 2022,38(8):129-139.
Aihua LI, Xiaobo WU, Chao CHEN, et al. Big data intelligent analysis technology for 5G network[J]. Telecommunications science, 2022, 38(8): 129-139.
李爱华, 吴晓波, 陈超, 等. 5G网络大数据智能分析技术[J]. 电信科学, 2022,38(8):129-139. DOI: 10.11959/j.issn.1000-0801.2022052.
Aihua LI, Xiaobo WU, Chao CHEN, et al. Big data intelligent analysis technology for 5G network[J]. Telecommunications science, 2022, 38(8): 129-139. DOI: 10.11959/j.issn.1000-0801.2022052.
摘 要:5G业务呈现形态多样化、需求个性化、体验极致化的特性,要求网络能够高效感知业务特性并满足业务需求;同时,5G切片、边缘计算、多接入协同等复杂技术的引入增加了端到端资源管理和调度的复杂性。5G核心网作为网络的拓扑中心和业务汇聚点,需融合人工智能技术,提升网络大数据分析能力,实现网络的自动化和智能化。首先介绍了国际标准化组织在5G网络智能化领域的研究进展,然后提出了5G网络大数据智能分析系统的架构及特征,最后进一步分析了网络大数据智能分析的3项潜在关键技术。
5G services are characterized by diversified forms
personalized requirements and extreme experience
which require the network to be able to efficiently perceive business characteristics and meet business requirements.Meanwhile
the introduction of complex technologies such as 5G slicing
edge computing and multi-access collaboration increases the complexity of end-to-end resource management and scheduling.As the network topology center and service convergence point
5G core network needs to integrate artificial intelligence technology
improve the ability of big data analysis
and realize the automation and intelligence of the network .The research progress of the international organization for standardization in the field of 5G network intelligence was firstly introduced
then the architecture and characteristics of 5G network big data intelligent analysis system was proposed
and the potential three key technologies of network big data intelligent analysis were finally further analyzed.
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