基于BP神经网络的5G覆盖三维化方案研究  

Research on 3D coverage scheme for 5G based on BP neural network

作　　者：高智涛 赖凯伦 刘旭 GAO Zhitao;LAI Kailun;LIU Xu(HeNan Province Infomation Consultation Designing Research CO.LTD,Zhengzhou 450008,China)

机构地区：[1]河南省信息咨询设计研究有限公司,河南郑州450000

出　　处：《长江信息通信》2024年第5期224-228,共5页Changjiang Information & Communications

摘　　要：针对楼宇内5G覆盖分层准确性差的问题,在依据高度数据分层的基础上,提出了一种基于气压值的分层方法,利用BP神经网络建立分析模型,精准定位5G网络室内采样点的海拔和楼层,实现楼宇5G覆盖的精准分析,为5G室内分布精准建设提供支撑。分析结果显示,在95%的置信水平下,与多元线性拟合函数、拉普拉斯压高方程相比,BP神经网络的标准误差值仅有0.000295,性能表现最优,能够有效提升5G覆盖分层的准确率。Aiming at the problem of poor accuracy in 5G coverage layering within buildings,a layering method based on air pressure values is proposed based on height data layering.A BP ncural network is used to establish an analysis model,accurately locate the altitude and floor of indoor sampling points in the 5G network,achieve accurate analysis of 5G coverage in build-ings,and provide support for the precise construction of 5G indoor distribution.The analysis results show that at a 95%confidence level,compared with the multivariate linear fitting func-tion and Laplace pressure cquation,the standard error value of the BP neural nctwork is only 0.000295,which shows the best performance and can effectively improve the accuracy of 5G coverage layering.

关 键 词：BP神经网络 大气压 气压传感器 温度 三维化 室分规划 

分 类 号：TN929.5[电子电信—通信与信息系统]