基于机器学习的蜂窝网络故障管理框架及方法综述  

Survey of cellular network fault management framework and methods based on machine learning

作　　者：雷泽临 苏俭[1] 郭伟[1] Lei Zelin;Su Jian;Guo Wei(National Key Laboratory of Science&Technology on Communications,University of Electronic Science&Technology of China,Chengdu 611731,China)

机构地区：[1]电子科技大学通信抗干扰技术国家级重点实验室,成都611731

出　　处：《计算机应用研究》2022年第12期3521-3533,共13页Application Research of Computers

基　　金：国家重点研发计划资助项目(2020YFB1807700)。

摘　　要：网络故障管理旨在检测、识别和纠正网络中发生的错误状况,为用户获得可靠稳定的网络服务提供保障,近年来,如何利用机器学习方法进行蜂窝网络故障管理引起了广泛关注。首先介绍了蜂窝网络故障管理的研究背景,明确网络故障管理的流程和功能;接着介绍现有蜂窝网络故障管理框架;随后对现有机器学习在蜂窝网络故障管理中的方法研究进行评述,从故障管理周期入手,分别对实现故障检测、故障诊断以及故障预测的机器学习方法展开介绍、总结和对比分析,为相关领域的研究提供参考。Network fault management aims to detect,identify and correct error conditions occurring in the network,providing users with reliable and stable network services.Recently,the utilization of machine learning methods for network fault mana-gement has attracted widespread attention.In this regard,this paper first introduced the research background of cellular network fault management and explained the process and function of network fault management,and then introduced the existing cellular network fault management frameworks.Subsequently,this paper reviewed the existing research on machine learning methods in cellular network fault management.Referring to the fault management lifecycle,this paper introduced,summarized and compared the machine learning methods for fault detection,fault diagnosis and fault prediction for the purpose of providing reference for research in related fields.

关 键 词：蜂窝网络 机器学习 故障管理 故障检测 故障诊断 故障预测 

分 类 号：TP306.3[自动化与计算机技术—计算机系统结构] TN929.5[自动化与计算机技术—计算机科学与技术]