Abstract
Mobile cellular networks have evolved into both data producers and data carriers. Big data analytics can enhance the operation of mobile cellular networks while increasing operator income. We present a unified data model based on random matrix theory and machine learning in this study. Following that, we provide an architectural framework for implementing big data analytics in mobile cellular networks. Furthermore, we discuss numerous illustrative cases in mobile cellular networks, such as huge signalling data, big traffic data, big location data, big radio waveforms data, and big heterogeneous data. Finally, we outline many open research problems in big data analytics in mobile cellular networks.
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