A New Method for End-to-End QoS Analysis of LTE Network in Focused Scene Based on Operator’s Big Data

Abstract

With the further development of the mobile network, telecom operators pay more and more attentions to end-to-end QoS (Quality of Service), like social application delay, in the focused scene. However, the conclusion based on the log tested at the scene or Key Performance Indicator (KPI) from the Operation and Maintenance Center (OMC) comes to inaccurate and inefficient. Our paper contributes a new method for analysis the end-to-end LTE network QoS in this area. Based on the operator’s big data, we firstly find out the “focused scene users” by using the identification algorithm, then we join the user side quality data in low latency, so we can analysis the end-to-end QoS of the scene we focused accurately and efficiently. Besides, it also powerfully supports optimization. The results also indicate that our new method is more efficient than the traditional ways.