摘要
随着5G网络的快速发展,网络创新技术方案不断更新迭代,快速高效地部署网络优化方案,并对网络中出现的重大故障能够免复现定位,是目前运营商和设备商面临的挑战。因此,设计了一种5G数字孪生实验室构建技术,通过外场场景化的模型学习,以及虚拟化数字孪生镜像平台构建,可以全生命周期地获取实际物理网络的运营状态。对于网络中出现的重大故障,通过时间的镜像回溯,达到免复现定位,并结合算法优化方案,生成网络优化策略,并部署在真实网络。
With the rapid development of 5G networks,the network innovation technology scheme is constantly updated and iterated,the network optimization scheme is deployed quickly and efficiently,and major faults in the network can be located without recurrence,which is the challenge faced by operators and equipment manufacturers at present.This paper proposes a 5G digital twin laboratory construction technology,which can obtain the operation state of the actual physical network in the whole life cycle through the model learning of outfield scene and the construction of virtual digital twin image platform.For major faults in the network,it can achieve non recurrence positioning through time image backtracking,and combined with the algorithm optimization scheme,generate network optimization strategy and deploy it in real network.
作者
游佳
YOU Jia(State Key Laboratory of Mobile Network and Mobile Multimedia Technology,Shenzhen Guangdong 518055,China)
出处
《通信技术》
2022年第5期605-609,共5页
Communications Technology
关键词
数字孪生
外场场景
模型学习
镜像回溯
digital twins
outfield scene infield
model learning
mirror backtracking