User awareness depth detection method based on MR and XDR

Abstract

The invention discloses a user awareness depth detection method based on MR and XDR, which comprises the following steps of S1, acquiring MR data and XDR data; S2, extracting user location informationfrom the XDR data; S3, by using the S1-MME interface data in the XDR data as a control plane and by using the S1-U interface data as a service plane, forming a service quality KQI index from the twodimensionalities including the control plane and the service plane; S4: establishing a scoring model of a user awareness MOS index, calculating a user awareness MOS value based on the scoring model and the service quality KQI index; S5, establishing a 'wireless performance-service performance-user awareness' three-layer analysis model according to a wireless performance KPI index, the service quality KQI index and the user awareness MOS value, and restoring the instantaneous wireless performance during poor quality of user awareness by the three-layer analysis model. The method, by means of the two-way linkage analysis between a wireless side and a service side, upgrades the analysis level of a poor-quality user from the cell level to the user level and improves the problem location accuracy and efficiency.

Description

technical field [0001] The invention belongs to the technical field of communication, and more specifically relates to a user perception depth detection method based on MR and XDR. Background technique [0002] Network quality is the lifeline of operators, and only good network service quality can ensure market share and market reputation. Good network coverage plays an extremely important role in ensuring the competitive advantage of network quality and user service experience. In recent years, with the rapid development of 4G services, users have increasingly stringent requirements for wireless network service quality. Therefore, how to quickly discover deep-seated problems in wireless networks, quickly locate problems and solve them in a timely manner, and improve the timeliness of network fault handling is particularly important. important. [0003] The evaluation and positioning of wireless network problems by traditional means only stays in the quantitative analysis ...

AI Technical Summary

Problems solved by technology

[0006] Aiming at at least one defect or improvement requirement of the prior art, the present invention provides a user perception depth detection method based on MR and signaling monitoring data (Circuit call and Packet call Detail Records, XDR), which solves the problems in the prior art As a user perception indicator, wireless performance KPI indicators cannot truly reflect user perception, and cannot truly restore real-time network quality issues that users complain about poor service perception.

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