Journal
IEEE ACCESS
Volume 4, Issue -, Pages 1985-1996Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2016.2540520
Keywords
Big data analytics; mobile cellular networks
Categories
Funding
- National Natural Science Foundation of China (NSFC) [61201224, 61471056, 61372089]
- Fundamental Research Funds for the Central Universities [DUT14QY44]
- China Jiangsu Future Internet Research Fund [BY2013095-3-1, BY2013095-3-03]
- Beijing Advanced Innovation Center for Future Internet Technology
- Natural Sciences and Engineering Research Council of Canada
- NSFC [61571296]
- National Science Foundation [ECCS-0901420, ECCS-0821658, CNS-1247778]
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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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