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.

Recent years have seen a quick improvement in the remote organization region. Up to this point remote systems administration has been centered around rapid and long reach applications. Be that as it may, there are numerous remote checking and control applications for modern and home conditions which require longer battery duration, lower information rates and less intricacy than those from existing principles. For such remote applications another standard called ZigBee has been created by the ZigBee Alliance. ZigBee is a mechanical standard made for Control and sensor organizations. It depends on the IEEE 802.15.4 norm. The IEEE 802.15.4 standard indicates the PHY Layer and MAC Layer for low information rate remote PANs. This paper incorporates ZigBee Alliance, IEEE 802.15.4 model, applications and benefits of ZigBee, future extent of ZigBee..