Big Data Analytics in Mobile Cellular Networks | Zendy

Ying He | Zendy; Fei Richard Yu | Zendy; Nan Zhao | Zendy; Hongxi Yin | Zendy; Haipeng Yao | Zendy; Robert C. Qiu | Zendy

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Big Data Analytics in Mobile Cellular Networks

Author(s) -

Ying He,

Fei Richard Yu,

Nan Zhao,

Hongxi Yin,

Haipeng Yao,

Robert C. Qiu

Publication year - 2016

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2016.2540520

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

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 traffic 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.

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