Dynamic uplink transmission scheduling for satellite Internet of Things applications

Satellite communication systems provide a cost-effective solution for global internet of things (IoT) applications due to its large coverage and easy deployment. This paper mainly focuses on Satellite networks system, in which low earth orbit (LEO) satellites network collect sensing data from the user terminals (UTs) and then forward the data to ground station through geostationary earth orbit (GEO) satellites network. Considering the limited uplink transmission resources, this paper optimizes the uplink transmission scheduling scheme over LEO satellites. A novel transmission scheduling algorithm, which combined Algorithms of Simulated Annealing and Monte Carlo (SA-MC), is proposed to achieve the dynamic optimal scheduling scheme. Simulation results show the effectiveness of the proposed SA-MC algorithm in terms of cost value reduction and fast convergence.