Guest Editorial: AI-Powered Telco Network Automation: 5G Evolution and 6G

被引:2
|
作者
Xin, Yan [1 ,2 ]
Yang, Kai [3 ,4 ]
Chih-Lin, I. [5 ]
Shamsunder, Sanyogita [6 ]
Lin, Xingqin
Lai, Lifeng [7 ,8 ]
机构
[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore, Singapore
[2] Samsung Res Amer Inc, Stand & Mobil Innovat Lab, Mountain View, CA 94043 USA
[3] Tongji Univ, Shanghai, Peoples R China
[4] Bell Labs, Murray Hill, NJ 07974 USA
[5] Stanford Univ, Stanford, CA USA
[6] Univ Virginia, Charlottesville, VA USA
[7] Worcester Polytech Inst, Worcester, MA USA
[8] Univ Arkansas, Fayetteville, AR USA
关键词
Special issues and sections; Cellular networks; 5G mobile communication; Automation; Artificial intelligence; Radio access networks; Communications technology;
D O I
10.1109/MWC.2023.10077118
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The fifth generation (5G) of cellular networks is significantly more complex than its predecessors due to several factors, such as increased cell density, differentiated service requirements, and coexistence with legacy networks. As a result, traditional operation and management (O&M) solutions, which heavily rely on human intervention, are no longer feasible to support such complex networks at reasonable operating expense (OPEX). Over the past few years, the telecommunication industry has come to the realization that leveraging artificial intelligence (AI) technology to enable a fully automated network O&M is a must to lowering OPEX and enhancing network key performance indicators (KPIs) for 5G, Beyond 5G (B5G), and the sixth generation (6G) of cellular networks. There have been numerous research efforts from both industry and academia to develop AI-powered network automation solutions. Many telecommunication operators and vendors have already adopted AI technology to automate some repetitive operational tasks and reduce reliance on personnel experience, such as cell planning, network deployment simplification, fault detection, and KPI optimization. While there has been notable progress for certain network O&M applications, the development of network automation solutions still faces several unique technical challenges that arise from telecommunication fields, including overwhelming network complexity, massive and diverse proprietary data, lack of industry-wide standards for radio access network (RAN) interfaces, and scarcity of labeled datasets.
引用
收藏
页码:68 / 69
页数:2
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