Airport network traffic prediction in 5G scenarios: a deep learning approach

Recently, the highly increasing number of mobile devices, higher data rate, and big data are pushing forward the rapid development of 5G. The network traffic of airports will explosively increase in the upcoming 5G era, which will cause challenges in providing fast and stable Internet service with passengers in airports. In this paper, we propose a novel approach to predict airport network traffic with deep learning in 5G scenarios. Based on Haikou Meilan International Airport, we collected real-world datasets of 4G cell traffic and used the Recurrent Neural Network (RNN) algorithm to process them to make network traffic prediction in the airport. Simulation results reveal that our method has good performance, and takes obvious advantage over traditional ones.