Dynamic Uplink Transmission Scheduling for Satellite Internet of Things Applications

作     者：Li Wang Shuaijun Liu Weidong Wang Zhiyan Fan Li Wang;Shuaijun Liu;Weidong Wang;Zhiyan Fan

作者机构：Beijing University of Posts and TelecommunicationsBeijing 100876China China Academy of Information and Communications TechnologyBeijing 100191China Institute of Software Chinese Academy of SciencesBeijing 100190China 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2020年第17卷第10期

页      面：241-248页

核心收录：

学科分类：1305[艺术学-设计学（可授艺术学、工学学位）] 080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 13[艺术学] 0809[工学-电子科学与技术（可授工学、理学学位）] 081104[工学-模式识别与智能系统] 08[工学] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 081001[工学-通信与信息系统] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 

基　　金：National High Technology Research and Development Program of China National Natural Science Foundation of China, NSFC 

主　　题：satellite IoT transmission scheduling resource allocation simulated annealing Monte Carlo 

摘      要：Satellite communication systems provide a cost-effective solution for global internet of things(IoT)applications due to its large coverage and easy *** 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 *** 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 *** results show the effectiveness of the proposed SA-MC algorithm in terms of cost value reduction and fast convergence.