基于信令监测的5G语音质差根因分析研究

Research on root cause analysis of 5G voice quality differences based on signaling monitoring

对现有VONR通话中存在的语音质量差问题,西南大区运营中心利用多接口原始信令消息,研究分析了5G语音业务质差原因,设计了一套检测质差场景的功能模块,该模块利用3sigma和决策树检测发现疑似质差指标,并融合匹配到的专家经验库生成质差定界结果、原因及处理建议,以告警工单的形式推送到运维人员。实验表明该模块能实时准确定位5G语音质差问题,智能化地形成解决方案,提高核心网网络优化效率。

In response to the problem of poor voice quality in existing VONR calls,the Southwest Regional Operations Center uti⁃lized multiple interfaces of raw signaling messages to study and analyze the reasons for poor quality of 5G voice services.A functional module was designed to detect poor quality scenarios.This module used 3Sigma and decision tree detection to identify suspected poor quality indicators,and fused the matched expert experience database to generate quality boundary results,reasons,and handling sugges⁃tions,Push to the operation and maintenance personnel in the form of an alarm work order.The experiment shows that this module can ac⁃curately locate 5G voice quality issues in real-time,intelligently form solutions,and improve the efficiency of core network optimization.