一种基于大数据的地铁用户感知监控系统

A metro user perception monitoring system based on big data

为提升地铁环境中用户网络感知,本文通过SEQ、LTE信令软采和PRS网管多维度数据融合,对地铁场景下的用户进行质差算法排查,综合评定用户在地铁场景下特定线路、特定站台和特定小区频点的体验和网络质量结果。通过质差门限设定将传统质差问题分析精确到具体用户和终端,为维护和优化人员精准处理问题提供依据,极大提高地铁场景问题处理效率和准确度。

This paper realizes the multi-dimensional data fusion of SEQ,LTE signaling soft mining and PRS network.By checking the quality difference algorithm of users in the subway scene,this paper comprehensive assessments the network quality results of users in specifi c lines,specifi c platforms and specific cell frequencies in the subway scene are comprehensively evaluated.The traditional quality problem analysis is accurated to specific users and terminals through the quality difference threshold setting,providing a basis for maintenance and optimization personnel to accurately handle problems,improve the effi ciency and accuracy of handling subway scene problems.