Early Warning of Core Network Capacity in Space-Terrestrial Integrated Networks

With the rapid development of low-orbit satellite communication networks both domestically and internationally, space-terrestrial integrated networks will become the future development trend. For space and terrestrial networks with limited resources, the utilization efficiency of the entire space-terrestrial integrated networks resources can be affected by the core network indirectly. In order to improve the response efficiency of core networks expansion construction, early warning of the core network elements capacity is necessary. Based on the integrated architecture of space and terrestrial network, multidimensional factors are considered in this paper, including the number of terminals, login users, and the rules of users' migration during holidays. Using artifical intelligence (AI) technologies, the registered users of the access and mobility management function (AMF), authorization users of the unified data management (UDM), protocol data unit (PDU) sessions of session management function (SMF) are predicted in combination with the number of login users, the number of terminals. Therefore, the core network elements capacity can be predicted in advance. The proposed method is proven to be effective based on the data from real network.