摘要
为了解决目前异网覆盖测评不准确、工作量大、效率低的问题,通过空间聚合、密度聚类等算法研究了异网覆盖智能测评方案,通过对4G异网覆盖测量数据分析了异网所有频点MR的监测、MR的最优RSRP提取、异网覆盖栅格指标的生成、异网问题区域的识别等关键技术,实验证实了异网覆盖智能测评的高度准确性及较高应用价值。
In order to solve the problems of low accuracy,heavy workload and inefficiency in the evaluation of heterogeneous network coverage,the intelligent evaluation solution is investigated based on the algorithms such as spatial aggregation and density clustering.Then this paper analyzes key technologies such as MR monitoring of all frequencies,optimal RSRP extraction of MR,generation of coverage grid index and automatic identification of problem areas in heterogeneous network through coverage measurement data in 4G heterogeneous network.The experiments demonstrate the high accuracy and high application value of intelligent evaluation of heterogeneous network coverage.
作者
许盛宏
宫云平
姚彦强
XU Shenghong;GONG Yunping;YAO Yanqiang(Strategy and Innovation Institute of China Telecommunications Co.,Ltd.,Guangzhou 510630,China;Guangdong Branch of China Telecommunications Co.,Ltd.,Guangzhou 5100811,China)
出处
《移动通信》
2020年第9期92-96,共5页
Mobile Communications
关键词
4G
大数据
异网覆盖
智能测评
4G
big data
heterogeneous network coverage
intelligent evaluation
