Cybertwin-Assisted Mode Selection in Ultra-Dense LEO Integrated Satellite-Terrestrial Network

Abstract

Ultra-dense low earth orbit (LEO) integrated satellite-terrestrial network (ULISTN) has become an emerging paradigm to support massive access of Internet of things (IoT) in beyond fifth generation mobile networks (B5G). In ULISTN, there are two communication modes: cellular mode and satellite mode, where IoT users assessing terrestrial small base stations (TSBSs) and terrestrial-satellite terminals (TSTs) respectively. However, how to optimize the network performance and guarantee self-interests of the operator and IoT users in ULISTN is a challenging issue. In this paper, we propose a cybertwin-assisted joint mode selection and dynamic pricing (JMSDP) scheme for effective network management in ULISTN, where cybertwin serves as the intelligent agent. In JMSDP, the operator determines optimal access prices of TSBSs and TSTs, while each user selects the access mode according to access prices. Specifically, the operator conducts the Stackelberg game aiming at maximizing average throughput depending on the mode selection results of IoT users. Meanwhile, IoT users as followers adopt the evolutionary game to choose an access mode based on the access prices provided by the operator. Simulation results show that the proposed JMSDP can improve the average throughput and reduce the delay effectively, comparing with random access (RA) and maximum rate access.