WHEN MACHINE LEARNING MEETS BIG DATA A Wireless Communication Perspective

被引:63
作者
Liu, Yuanwei [1 ]
Bi, Suzhi [2 ]
Shi, Zhiyuan [3 ]
Hanzo, Lajos [4 ]
机构
[1] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London, England
[2] Shenzhen Univ, Coll Elect & Informat Engn, Shenzhen, Peoples R China
[3] Onfido Res London, London, England
[4] Univ Southampton, Sch Elect & Comp Sci, Southampton, Hants, England
来源
IEEE VEHICULAR TECHNOLOGY MAGAZINE | 2020年 / 15卷 / 01期
基金
欧盟地平线“2020”;
关键词
NETWORKS;
D O I
10.1109/MVT.2019.2953857
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We have witnessed an exponential growth in commercial data services, which has led to the so-called big data era. Machine learning, one of the most promising artificial intelligence (AI) tools for analyzing this deluge of data, has been called upon in many industry and academic research areas. In this article, we briefly review big data analysis and machine learning, along with their potential applications in next-generation (NG) wireless networks. Next, we invoke big data analysis to predict the requirements of mobile users and exploit such analysis to improve the performance of "social network-aware wireless." In particular, a unified, big data-aided machinelearning framework is proposed that consists of feature extraction, data modeling, and prediction/online refinement. The main benefits of this proposed framework are that, by relying on big data that reflects both the spectral and other challenging requirements of users, we can refine the motivation, problem formulations, and methodology of powerful machine-learning algorithms in the context of wireless networks. © 2005-2012 IEEE.
引用
收藏
页码:63 / 72
页数:10
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