4.6 Article

Big Data Analytics in Mobile Cellular Networks

Journal

IEEE ACCESS
Volume 4, Issue -, Pages 1985-1996

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2016.2540520

Keywords

Big data analytics; mobile cellular networks

Funding

  1. National Natural Science Foundation of China (NSFC) [61201224, 61471056, 61372089]
  2. Fundamental Research Funds for the Central Universities [DUT14QY44]
  3. China Jiangsu Future Internet Research Fund [BY2013095-3-1, BY2013095-3-03]
  4. Beijing Advanced Innovation Center for Future Internet Technology
  5. Natural Sciences and Engineering Research Council of Canada
  6. NSFC [61571296]
  7. National Science Foundation [ECCS-0901420, ECCS-0821658, CNS-1247778]

Ask authors/readers for more resources

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.

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