Artificial Intelligence to Manage Network Traffic of 5G Wireless Networks

被引：83

作者：

Fu, Yu ^{[1
]}

Wang, Sen ^{[2
]}

Wang, Cheng-Xiang ^{[1
,4
]}

Hong, Xuemin ^{[5
]}

McLaughlin, Stephen ^{[3
]}

机构：

[1] Heriot Watt Univ, Edinburgh, Midlothian, Scotland

[2] Heriot Watt Univ, Robot & Autonomous Syst, Edinburgh, Midlothian, Scotland

[3] Heriot Watt Univ, Sch Engn & Phys Sci, Edinburgh, Midlothian, Scotland

[4] Southeast Univ, Nanjing, Jiangsu, Peoples R China

[5] Xiamen Univ, Xiamen, Peoples R China

来源：

IEEE NETWORK | 2018年 / 32卷 / 06期

基金：

英国工程与自然科学研究理事会; 欧盟地平线“2020”;

关键词：

CHALLENGES;

D O I：

10.1109/MNET.2018.1800115

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The deployment of 5G wireless communication systems is projected to begin in 2020. With new scenarios, new technologies, and new network architectures, the traffic management for 5G networks will present significant technical challenges. In recent years, AI technologies, especially ML technologies, have demonstrated significant success in many application domains, suggesting their potential to help solve the problem of 5G traffic management. In this article, we investigate the new characteristics of 5G wireless network traffic and discuss challenges they present for 5G traffic management. Potential solutions and research directions for the management of 5G traffic, including distributed and lightweight ML algorithms and a novel AI assistant content retrieval algorithm framework, are discussed.

引用

页码：58 / 64

页数：7

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