基于强化学习的应急通信研究  

Research on Emergency Communication Based on Reinforcement Learning

作　　者：朱连伟 ZHU Lian-wei(School of Management Science and Engineering,Anhui University of Technology,Ma’anshan 243032)

机构地区：[1]安徽工业大学管理科学与工程学院,马鞍山243032

出　　处：《现代计算机》2020年第30期8-11,共4页Modern Computer

摘　　要：随着信息技术的发展和普及,人们的生活越来越加的便利,但同时也越来越依靠通信的便利,所以在遭遇自然灾害而导致地面的基础通讯设施损坏会给人们的生活以及救援带来十分大的影响。虽然现在对于应急通信方面也有卫星和通信车等应急方式,但是由于其本身的特点很难满足灾区现场的大量用户的通信需求。所以拥有高机动性和低成本的无人机和布置方便灵活的无线自组网络便进入研究人员的视野。而随着AlphaGo的出现和发展,强化学习也越来越受到研究人员的关注,将强化学习应用于基于无人机的应急通信系统,能够很好地应用无人机的移动性来优化通信网络。With the development and popularization of information technology,people's lives are becoming more and more convenient,but at the same time,they are increasingly relying on the convenience of communication.Therefore,the damage to the basic communication facilities on the ground caused by natural disasters will have a great impact on people's lives and rescue.Although there are also emergency methods such as satellites and communication vehicles for emergency communications,it is difficult to meet the communication needs of a large number of users in the disaster area due to its own characteristics.Therefore,the UAV with high mobility and low cost and the wireless ad hoc network with convenient and flexible layout have entered the vision of researchers.With the emergence and development of AlphaGo,reinforcement learning has also attracted more and more attention from researchers.The application of reinforcement learning to emergency communication systems based on drones can well apply the mobility of drones to optimize communication networks.

关 键 词：强化学习 无人机 应急通信 无线自组网络 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] V279[自动化与计算机技术—控制科学与工程]