The 5G IoT is very complicated and there are many factors that affect the network performance. Presently, the optimization of network is still the focus of research. Although the existing literature has done a large number of researches in this aspect, there have always been problems, such as complex algorithms. Based on the previous research, we propose a big data mining analysis method, which improves the comprehensive performance of the network by analyzing the relationship of massive data variables so as to optimize the combination of the network. In this paper, according to each of terminal variables at any moment such as power consumption, bandwidth, noise power, subcarrier bandwidth, interference power and coding efficiency, etc. we develop the mathematical modeling of principal component multiple regression. Then we simulate this scheme by edge computing technology and combine it with intelligent algorithms. The research results show that this method can effectively predict the data concerned, and the residual is the smallest. Therefore, the research provides an important basic for application of the approach to the mobile edge network optimization of IoTs.

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The commercialization of the fifth-generation technology and the rapid development of Internet of Things technology have made mobile communication networks increasingly complex. Simultaneously, the massive terminal connections have caused serious interference between networks. Large-scale array antennas have become a hot topic of recent studies to improve the wireless transmission characteristics and spectrum resource utilization efficiency. This study was aimed at exploring using large-scale array antennas combined with neural networks in ultradense cells to improve the wireless signal transmission quality. The simulation results showed that the scheme realized not only the wireless signal transmission with a neural network but also the effective recovery of the source signal. Similarly, the application of this scheme effectively reduced the power consumption during signal transmission, the delay, and the interference.