光通信研究Issue(2)：33-39,7.DOI:10.13756/j.gtxyj.2025.240040
FSO通信系统中应用机器学习算法的研究进展
Research Progress of Machine Learning Algorithms Applied in FSO Communication Systems
摘要
Abstract
Free-Space Optical(FSO)communication,as an effective transmission technology with high speed,low latency,large bandwidth,and support for rapid link deployment,has been increasingly valued in the field of wireless communication aimed at big data transmission in recent years.However,the communication performance of FSO signal link is susceptible to weather conditions and atmospheric states(especially atmospheric turbulence),resulting in degradation of signal reception and transmis-sion quality as well as system performance.In order to enhance the reception,transmission,and overall performance of FSO com-munication systems,researchers have begun to apply various advanced machine learning algorithms to optimize the signal detec-tion and channel modeling processes in FSO communication systems.In this article,the research progress of applying typical ma-chine learning algorithms in FSO communication systems in signal detection,channel estimation,auxiliary optical compensation,and other aspects are reviewed.We compare and analyze the application characteristics of different typical machine learning algo-rithms,and discuss the future development trends of applying machine learning algorithms in FSO communication systems.关键词
自由空间光通信/机器学习/大气衰减/信号检测Key words
FSO communication/machine learning/atmospheric attenuation/signal detection分类
电子信息工程引用本文复制引用
柳海楠,邵宇丰,王安蓉,朱耀东,杨林捷,陈超,李文臣,胡文光..FSO通信系统中应用机器学习算法的研究进展[J].光通信研究,2025,(2):33-39,7.基金项目
重庆市基础研究与前沿探索资助项目(cstc2018jcyjAX0038,cstc2016jcyjA0246) （cstc2018jcyjAX0038,cstc2016jcyjA0246）
重庆市教委科学技术研究计划重大资助项目(KJZD-M201901201) （KJZD-M201901201）
国家自然科学基金资助项目(61107064) （61107064）
浙江省重点研发计划资助项目(2017C01043) （2017C01043）
