5G网络大数据智能分析技术

doi:10.11959/j.issn.1000-0801.2022052

Abstract

Abstract:

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.

Key words: 5G network, artificial intelligence, network big data, intelligent analysis

CLC Number:

TP393

Aihua LI, Xiaobo WU, Chao CHEN, Bin WEI, Yuanyuan SHI. Big data intelligent analysis technology for 5G network[J]. Telecommunications Science, 2022, 38(8): 129-139.

Figures/Tables 14

References 26

[1]	3GPP. System architecture for the 5G system (5GS):TS 23.501[S]. 2021.
[2]	3GPP. 5G system; network data analytics services:TS 23.520[S]. 2021.
[3]	3GPP. 5G system; architecture enhancements for 5G system (5GS) to support network data analytics service:TS 23.288[S]. 2021.
[4]	3GPP. 3rd Generation Partnership Project; technical specification group services and system aspects; architecture enhancements for 5G system(5GS) to support network data analytics services (Release 16):TS23.288 V16.4.0[S]. 2020.
[5]	3GPP. 3rd Generation Partnership Project; technical specification group services and system aspects; study on enablers for network automation for 5G system(5GS); phase2 (Release 17) TR 23.700-91 V0.4.0[R]. 2020.
[6]	3GPP. Study on architecture for next generation system (Release 14):TR23.799,V1.0.1[S]. 2016.
[7]	ITU-R. Recommendation ITU-R M.2083:IMT vision-framework and overall objectives of the future development of IMT for 2020 and beyond[S]. 2015.
[8]	ITU-T. Architectural framework for machine learning in future networks including IMT-2020:Y.3172[S]. 2019.
[9]	ITU-T. Framework for data handling to enable machine learning in future networks including IMT-2020:Y.3174[S]. 2020.
[10]	IMT-2020(5G)推进组. 5G 网络架构设计白皮书[R]. 2016.
	IMT-2020 (5G) Propulsion Group. White paper of 5G network architecture design[R]. 2016.
[11]	IMT-2020. 5G 网络技术架构[R]. 2015.
	IMT-2020. 5G network technology architecture[R]. 2016.
[12]	李爱华, 何伟, 杨爱东 ,等. 移动通信网络中的联邦学习白皮书[[R]. 2021.
	LI A H , HE W , YANG A D ,et al. White paper on federated learning in mobile communication networks[R]. 2021.
[13]	China Mobile Research Institute. White paper of NGFI (next generation fronthaul interface) version 1.0[R]. 2015.
[14]	马瑞涛, 王光全, 任驰 ,等. 3GPP R16 5G核心网标准及关键技术研究[J]. 电子技术应用, 2020,46(11): 30-35,40.
	MA R T , WANG G Q , REN C ,et al. Study on 3GPP R16 5G core network standards and key technology[J]. Application of Electronic Technique, 2020,46(11): 30-35,40.
[15]	谢娟 . 浅析 5G 核心网关键技术及现网演进策略[J]. 移动信息, 2019(6): 15-17.
	XIE J . Analysis on key technologies of 5G core network and current network evolution strategy[J]. Mobile Information, 2019(6): 15-17.
[16]	杨旭, 肖子玉, 梁冰 ,等. 5G 核心网部署及演进方案[J]. 电信科学, 2020,36(9): 131-140.
	YANG X , XIAO Z Y , LIANG B ,et al. 5G core network deployment and evolution scheme[J]. Telecommunications Science, 2020,36(9): 131-140.
[17]	马洪源, 肖子玉, 卜忠贵 . 5G 标准及产业进展综述[J]. 电信工程技术与标准化, 2018(3): 23-27.
	MA H Y , XIAO Z Y , BU Z G . 5G standard and industry progress review[J]. Telecom Engineering Technics and Standardization, 2018(3): 23-27.
[18]	杨旭, 肖子玉, 邵永平 ,等. 面向 5G 的核心网演进规划[J]. 电信科学, 2018,34(7): 162-170.
	YANG X , XIAO Z Y , SHAO Y P ,et al. Core network evolution planning oriented 5G[J]. Telecommunications Science, 2018,34(7): 162-170.
[19]	尤肖虎, 张川, 谈晓思 ,等. 基于AI的5G技术:研究方向与范例[J]. 中国科学:信息科学, 2018,48(12): 1589-1602.
	YOU X H , ZHANG C , TAN X S ,et al. AI for 5G:research directions and paradigms[J]. Scientia Sinica (Informationis), 2018,48(12): 1589-1602.
[20]	The FATE Authors. Federated AI technology enabler[Z]. 2019.
[21]	BEUTEL D J , TOPAL T , MATHUR A ,et al. Flower:a friendly federated learning research framework[Z]. 2020.
[22]	杨强 . AI与数据隐私保护：联邦学习的破解之道[J]. 信息安全研究, 2019,5(11): 961-965.
	YANG Q . AI and data privacy protection:the way to federated learning[J]. Journal of Information Security Research, 2019,5(11): 961-965.
[23]	The Linux Foundation. Open neural network exchange (ONNX)[Z]. 2022.
[24]	申洁 . 基于 DPI 技术的数据业务分析及网络优化[D]. 北京:华北电力大学, 2016.
	SHEN J . Data service analysis and network optimization based on DPI technology[D]. Beijing:North China Electric Power University, 2016.
[25]	陈贞贞 . 基于 DPI 和机器学习的加密流量类型识别研究[J]. 信息通信, 2018(4): 3.
	CHEN Z Z . Research on encrypted traffic type recognition based on DPI and machine learning[J]. Information Communication, 2018(4): 3.
[26]	许勇刚, 刘宏宇, 闵云浪 . 一种基于 DPI 技术的网络数据安全性分析系统及方法:CN 105491018 A[P]. 2015.
	XU Y G , LIU H Y , MIN Y L . Network data security analysis system and method based on DPI technology:CN 105491018 A[P]. 2015.

Metrics

Recommended 0

No Suggested Reading articles found!

数据	数据源	描述
SUPI	SMF	终端标识
S-NSSAI	SMF	切片
DNN	SMF	DNN
start/end time	SMF	起始/结束时间
data volume	SMF	流量大小（UL/DL）
data duration	SMF	流量时长（UL/DL）
QoS flow bit rate	SMF	观测带宽（UL/DL）
packet transmission	SMF	观测包个数（每个UL/DL）
payload packets	SMF	用户面数据包收集

流量信息	业务标识
Traffic Data 1	App ID 1
Traffic Data 2	App ID 2
Traffic Data 3	App ID 1
Traffic Data 4	App ID 3
…	…
Traffic Data N	App ID 2

Big data intelligent analysis technology for 5G network

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 14

References 26

Related Articles 15

Metrics

Recommended 0

[1]	Zehua GUO, Haowen ZHU, Tongwen XU. Network modal innovation for distributed machine learning [J]. Telecommunications Science, 2023, 39(6): 44-51.
[2]	Ruihong JIANG, Yizhe FENG, Yaohua SUN, Haina ZHENG. A survey on networking key technologies for LEO satellite network [J]. Telecommunications Science, 2023, 39(2): 37-47.
[3]	Hong SHEN, Ling CUI, Tiankui ZHANG. Research on 5G network deployment scheme for intelligent manufacturing [J]. Telecommunications Science, 2022, 38(Z1): 158-163.
[4]	Yejiang ZHANG, Lei SUN, Yiyan YIN, Xiaokang YANG, Jian HU. Research on the application of 700 MHz frequency band in 5G network optimization [J]. Telecommunications Science, 2022, 38(6): 156-163.
[5]	Xin TAO, Junqing WAN, Yifeng LI, Xisheng XU, Nanting QIAO, Bin XU. Research on simulation of 5G indoor distribution system based on ray tracing propagation model [J]. Telecommunications Science, 2022, 38(2): 111-118.
[6]	Mingwei ZHU. AI engineering technology solutions in network intelligence [J]. Telecommunications Science, 2022, 38(2): 157-165.
[7]	Ruiying CHENG, Pan ZHANG, Yu XIAO, Yujie QIAO, Anyi ZHANG. Time series data based AI operation and maintenance system of cloud network collaboration platform [J]. Telecommunications Science, 2022, 38(11): 24-35.
[8]	Zhihong CHEN, Mingxiao WANG. Application of computer vision in intelligent security [J]. Telecommunications Science, 2021, 37(8): 142-147.
[9]	Shuo YUAN, Yijing REN, Zeyu WANG, Yaohua SUN, Mugen PENG. Software defined intelligent satellite-terrestrial integrated wireless network [J]. Telecommunications Science, 2021, 37(6): 66-77.
[10]	Jianwu ZHANG, Luxin WANG, Lingfen SUN, Qianye ZHANG, Hangguan SHAN. An survey on application of artificial intelligence in 5G system [J]. Telecommunications Science, 2021, 37(5): 14-31.
[11]	Zhiyong LIU, Zhongjiang HE, Yilong RUAN, Junfeng SHAN, Chao ZHANG. Big data security features and operation practices [J]. Telecommunications Science, 2021, 37(5): 160-169.
[12]	Junhui ZHAO, Danyang ZHANG, Lin HE. Analysis and prospect of communication technology in smart urban rail [J]. Telecommunications Science, 2021, 37(4): 1-13.
[13]	Guobin XU, Zhewei FU, Ming LIU, Zhiji DENG, Cungang WANG, Guanghai ZHONG, Hui LI, Wei MENG, Yunjie WU. Research on 5G upstream bandwidth detection technology and application [J]. Telecommunications Science, 2021, 37(12): 51-59.
[14]	Yuting WU, Xuliang WANG, Shuo QUAN. KubeTelecom: a multi-cloud multi-container cluster management and operation engine for 5G network slicing [J]. Telecommunications Science, 2021, 37(12): 72-83.
[15]	Yan ZHANG. Networking technology and implementation method based on 5G slice private line [J]. Telecommunications Science, 2021, 37(10): 143-151.