基于大数据的5G基站退服成本估算  

The cost estimation of 5G base station decommission based on big data

作　　者：魏鹏涛 曾宇[1] 王海宁[1] 李皛 姚沛君 李梦池 徐艺谋 Wei Pengtao;Zeng Yu;Wang Haining;Li Xiao;Yao Peijun;Li Mengchi;Xu Yimou(Network AI Research Center,Research Institute of Emerging Information Technology,Institute of Strategic and Innovative Research of China Telecom Co.,Ltd.,Beijing 102209,China)

机构地区：[1]中国电信股份有限公司战略与创新研究院新兴信息技术研究所网络AI研究中心

出　　处：《电子技术应用》2019年第10期14-18,共5页Application of Electronic Technique

摘　　要：随着5G技术的快速发展,5G基站的数量和密度将远超4G,基站的建设和维护也成为不可忽视的问题。因此,全面分析了5G基站退服情况,并提出一种基于大数据的5G基站退服成本估算方案。凭借基站历史退服数据,采用LSTM神经网络建立基站退服预测模型,然后构建了5G基站退服成本估算模型,对预测的5G基站退服进行成本估算。最后通过实验分析,说明了方案的有效性,并提出建议。With the rapid development of 5G technology, the number and density of 5G base stations will be far higher than 4G,and the construction and maintenance of base stations will become a problem that cannot be ignored. Therefore, this paper comprehensively analyzes the 5G base station decommission situation and puts forward a 5G base station decommission cost estimation scheme based on big data. With the base station historical decommission data, the LSTM neural network is used to establish the base station decommission prediction model. Then the 5G base station decommission cost estimation model is constructed, and the cost estimation of the forecast 5G base station decommission is made. Finally, through the experimental analysis, the effectiveness of the scheme is explained and suggestions are put forward.

关 键 词：大数据 5G 基站退服 成本估算 

分 类 号：TN929.5[电子电信—通信与信息系统]