Research on 5G core network service model intelligent prediction

Nan FENG; Helin LIU; Quan ZHOU; Haijun YANG; Mineng FU; Daping ZHONG

doi:10.11959/j.issn.1000-0801.2022046

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Research on 5G core network service model intelligent prediction

Research and Development | 更新时间：2024-06-05

- Research on 5G core network service model intelligent prediction
- Telecommunications Science Vol. 38, Issue 8, Pages: 111-119(2022)
- 作者机构：
  
  1. 中国移动通信有限公司研究院，北京 100053
  2. 中国移动通信集团有限公司，北京 100032
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2022046
  CLC： TN915
- Published Online：2022-08，
  
  Published：20 August 2022
- 稿件说明：
移动端阅览
Nan FENG, Helin LIU, Quan ZHOU, et al. Research on 5G core network service model intelligent prediction[J]. Telecommunications science, 2022, 38(8): 111-119.
DOI：

Nan FENG, Helin LIU, Quan ZHOU, et al. Research on 5G core network service model intelligent prediction[J]. Telecommunications science, 2022, 38(8): 111-119. DOI： 10.11959/j.issn.1000-0801.2022046.

摘要

摘要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。

Abstract

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references

ALUIGI L , ORECCHINI G , LARCHER L . A 28 GHz scalable beamforming system for 5G automotive connectivity:an integrated patch antenna and power amplifier solution [C ] // Proceedings of 2018 IEEE MTT-S International Microwave Workshop Series on 5G Hardware and System Technologies . Piscataway:IEEE Press , 2018 : 1 - 3 .

运行监测协调局 . 2021年1-7月通信业经济运行情况 [EB ] . 2021 .

Operational Monitoring and Coordination Bureau . Economic operation of the communications industry from January to July 2021 [EB ] . 2021 .

石红晓 , 程永志 . 基于 5G 核心网的网络演进及策略研究 [J ] . 通信与信息技术 , 2020 ( 4 ): 39 - 41 , 50 .

SHI H X , CHENG Y Z . Research on network evolution and strategy based on 5G core network [J ] . Communication ＆ Information Technology , 2020 ( 4 ): 39 - 41 , 50 .

BEEREDDY S , SIRUPA K . NFV use case—Delivering virtual CPE with multi-vendor VNF orchestration [C ] // Proceedings of 2015 IEEE Conference on Network Function Virtualization and Software Defined Network . Piscataway:IEEE Press , 2015 : 25 - 27 .

MA L , WEN X M , WANG L H , et al . An SDN/NFV based framework for management and deployment of service based 5G core network [J ] . China Communications , 2018 , 15 ( 10 ): 86 - 98 .

梁雪梅 , 方晓农 , 朱林 . 3GPP R15冻结后的5G核心网关键技术研究 [J ] . 通信与信息技术 , 2018 ( 6 ): 33 - 35 , 70 .

LIANG X M , FANG X N , ZHU L . Research on key technologies of 5G core network after 3GPP R15 freeze [J ] . Communication ＆ Information Technology , 2018 ( 6 ): 33 - 35 , 70 .

嵇夏 . 基于大数据的分组域容量分析系统设计与实现 [J ] . 电信快报 , 2018 ( 11 ): 28 - 32 .

JI X . System designing and implementing of packet switch domain capacity analysis based on big data [J ] . Telecommunications Information , 2018 ( 11 ): 28 - 32 .

吕红卫 , 冯征 . 核心网分组域引入EPC架构分析 [J ] . 电信科学 , 2010 , 26 ( 6 ): 116 - 120 .

LYU H W , FENG Z . Analysis of the introduction of EPC into the core network packet domain [J ] . Telecommunication Science , 2010 , 26 ( 6 ): 116 - 120 .

雒江涛 , 李晴川 . 基于云存储的分组域监测系统 [J ] . 重庆邮电大学学报(自然科学版) , 2012 , 24 ( 6 ): 675 - 681 .

LUO J T , LI Q C . Packet domain monitoring system based on cloud storage [J ] . Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition) , 2012 , 24 ( 6 ): 675 - 681 .

3GPP . General packet radio service (GPRS) enhancements for evolved universal terrestrial radio access network (E-UTRAN) access Release 8:TS 23.401 [S ] . 2015 .

黄海 , 周灵 . 基于曲线拟合的分组域业务分析模型及算法实现 [J ] . 现代计算机(专业版) , 2016 ( 23 ): 16 - 19 .

HUANG H , ZHOU L . Model and algorithm for capacity analysis in packet switch based on curve fitting [J ] . Modern Computer , 2016 ( 23 ): 16 - 19 .

袁野 , 孙迪科 , 张荣 . 网络融合背景下的移动分组域网络负荷指标关联模型研究 [J ] . 移动通信 , 2015 , 39 ( 2 ): 34 - 39 .

YUAN Y , SUN D K , ZHANG R . Research on correlation model of network load index in mobile packet domain for integrated network [J ] . Mobile Communications , 2015 , 39 ( 2 ): 34 - 39 .

ISTIAKE SUNNY M A , MASWOOD M M S , ALHARBI A G . Deep learning-based stock price prediction using LSTM and Bi-directional LSTM model [C ] // Proceedings of 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES) . Piscataway:IEEE Press , 2020 : 87 - 92 .

KUMAR S D , SUBHA D . Prediction of depression from EEG signal using long short term memory(LSTM) [C ] // Proceedings of 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI) . Piscataway:IEEE Press , 2019 : 1248 - 1253 .

DAOUD N , ELTAHAN M , ELHENNAWI A . Aerosol optical depth forecast over global dust belt based on LSTM,CNN-LSTM,CONV-LSTM and FFT algorithms [C ] // Proceedings of IEEE EUROCON 2021 - 19th International Conference on Smart Technologies . Piscataway:IEEE Press , 2021 : 186 - 191 .

王艺霏 , 于雷 , 滕飞 , 等 . 基于长-短时序特征融合的资源负载预测模型 [J ] . 计算机应用 , 2021 .

WANG Y F , YU L , TENG F , et al . Resource-load prediction model based on long-short time series feature fusion [J ] . Journal of Computer Applications , 2021 .

ZHU H X , LU X H . The prediction of PM2.5 value based on ARMA and improved BP neural network model [C ] // Proceedings of 2016 International Conference on Intelligent Networking and Collaborative Systems (INCoS) . Piscataway:IEEE Press , 2016 : 515 - 517 .

NARENDRA BABU C , ESWARA REDDY B . Predictive data mining on Average Global Temperature using variants of ARIMA models [C ] // Proceedings of IEEE-International Conference on Advances In Engineering,Science and Management (ICAESM -2012) . Piscataway:IEEE Press , 2012 : 256 - 260 .

NOUREEN S , ATIQUE S , ROY V , et al . Analysis and application of seasonal ARIMA model in Energy Demand Forecasting:a case study of small scale agricultural load [C ] // Proceedings of 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems . Piscataway:IEEE Press , 2019 : 521 - 524 .

CHOI D J , HAN J H , PARK S U , et al . Comparative study of CNN and RNN for motor fault diagnosis using deep learning [C ] // Proceedings of 2020 IEEE 7th International Conference on Industrial Engineering and Applications . Piscataway:IEEE Press , 2020 : 693 - 696 .

王振业 , 叶成绪 , 王文韬 , 等 . 基于LSTM-Att方法的音乐流行趋势预测 [J ] . 计算机技术与发展 , 2020 , 30 ( 9 ): 188 - 193 .

WANG Z Y , YE C X , WANG W T , et al . Music trend forecast based on LSTM-att method [J ] . Computer Technology and Development , 2020 , 30 ( 9 ): 188 - 193 .

AKANDEH A , SALEM F M . Slim LSTM networks:LSTM_6 and LSTM_C6 [C ] // Proceedings of 2019 IEEE 62nd International Midwest Symposium on Circuits and Systems . Piscataway:IEEE Press , 2019 : 630 - 633 .

任君明 . 基于数据挖掘技术的移动通信话务预测模型 [J ] . 电信工程技术与标准化 , 2015 , 28 ( 6 ): 79 - 82 .

REN J M . Discussion on mobile communication traffic forecasting model based on data mining technology [J ] . Telecom Engineering Technics and Standardization , 2015 , 28 ( 6 ): 79 - 82 .

欧大春 . 5G 时代利用人工智能提升运营商网络竞争力的研究 [J ] . 邮电设计技术 , 2020 ( 10 ): 1 - 4 .

OU D C . Research on using artificial intelligence to improve network competitiveness of operators in 5G era [J ] . Designing Techniques of Posts and Telecommunications , 2020 ( 10 ): 1 - 4 .

韩炳涛 , 屠要峰 , 王永成 , 等 . 人工智能技术助力通信网络智能化升级 [J ] . 人工智能 , 2021 , 8 ( 1 ): 107 - 116 .

HAN B T , TU Y F , WANG Y C , et al . Artificial intelligence technology helps the intelligent upgrade of communication networks [J ] . AI-View , 2021 , 8 ( 1 ): 107 - 116 .

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