Big Data Analytics in Mobile Cellular Networks

被引：99

作者：

He, Ying ^{[1
]}

Yu, Fei Richard ^{[2
]}

Zhao, Nan ^{[1
]}

Yin, Hongxi ^{[1
]}

Yao, Haipeng ^{[3
]}

Qiu, Robert C. ^{[4
,5
,6
]}

机构：

[1] Dalian Univ Technol, Dept Informat & Commun Engn, Dalian 116024, Peoples R China

[2] Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON K1S 5B6, Canada

[3] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China

[4] Shanghai Jiao Tong Univ, Dept Elect Engn, Res Ctr Big Data Engn & Technol, Shanghai 200240, Peoples R China

[5] Shanghai Jiao Tong Univ, Dept Elect Engn, State Energy Smart Grid Res & Dev Ctr, Shanghai 200240, Peoples R China

[6] Tennessee Technol Univ, Dept Elect & Comp Engn, Cookeville, TN 38505 USA

来源：

IEEE ACCESS | 2016年 / 4卷

基金：

加拿大自然科学与工程研究理事会; 美国国家科学基金会; 中国国家自然科学基金;

关键词：

Big data analytics; mobile cellular networks; SOFTWARE-DEFINED NETWORKING; RANDOM MATRICES;

D O I：

10.1109/ACCESS.2016.2540520

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Mobile cellular networks have become both the generators and carriers of massive data. Big data analytics can improve the performance of mobile cellular networks and maximize the revenue of operators. In this paper, we introduce a unified data model based on the random matrix theory and machine learning. Then, we present an architectural framework for applying the big data analytics in the mobile cellular networks. Moreover, we describe several illustrative examples, including big signaling data, big trafic data, big location data, big radio waveforms data, and big heterogeneous data, in mobile cellular networks. Finally, we discuss a number of open research challenges of the big data analytics in the mobile cellular networks.

引用

页码：1985 / 1996

页数：12

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