A SON Decision-Making Framework for Intelligent Management in 5G Mobile Networks

被引:0
|
作者
Jiang, Wei [1 ,2 ]
Strufe, Mathias [1 ]
Schotten, Hans D. [1 ,2 ]
机构
[1] German Res Ctr Artificial Intelligence, DFKI, Kaiserslautern, Germany
[2] Univ Kaiserslautern, Dept Elect & Comp Engn, Kaiserslautern, Germany
基金
欧盟地平线“2020”;
关键词
5G; artificial intelligence; machine learning; network management; self-organized network;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The 5th Generation (5G) mobile system is envisioned to become more complicated and heterogeneous to meet the radical Key Performance Indicators specified in ITU-R IMT-2020. It imposes a great challenge on today's manual and semi-automated network management in 3G/4G systems. Taking advantage of cutting-edge technologies in the area of Artificial Intelligence and Self-Organized Network (SON), the concept of intelligent network management provides an effective solution and therefore attracts the attention of 5G research community. In this paper, a SON decision-making framework is proposed to provide a possible method to realize intelligent management for the upcoming 5G networks. Two complementary decision-making approaches, namely Rule-based and Machine Learning-based intelligence, their interactions, and lifecycle management of intelligence slices are presented. Moreover, the setup of a wireless network test-bed, as well as some experimental results to verify the effectiveness of the proposed framework, are illustrated.
引用
收藏
页码:1158 / 1162
页数:5
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