Mobile communication network data analysis method and device and computer storage medium

Abstract

The invention discloses a mobile communication network data analysis method, apparatus and device, and a computer storage medium. The method comprises the steps: determining a plurality of base station cells covered by a mobile communication network corresponding to a high-speed traffic line; extracting user identifiers in a plurality of base station cells to obtain a cell user list; screening user identifiers meeting preset high-speed traffic line user conditions from the cell user list to obtain a high-speed user list; acquiring signaling data corresponding to each user identifier in the high-speed user list from a signaling platform according to the high-speed user list; based on each user identifier in the high-speed user list and the corresponding signaling data, performing mobile communication network data analysis corresponding to the high-speed traffic line to obtain an analysis result. According to the method disclosed in the embodiment of the invention, the pertinence and accuracy of mobile communication network analysis corresponding to the high-speed traffic line and subsequent optimization according to the analysis result can be improved.

Description

technical field [0001] The invention belongs to the technical field of mobile communication network optimization, and in particular relates to a mobile communication network data analysis method, device, equipment and computer storage medium. Background technique [0002] The mobile communication network corresponding to the high-speed traffic line belongs to the mobile communication network in the special scene of high-speed movement. The time is very short, the quality of the communication link is easy to deteriorate, and the measurement and signaling interaction time required for the communication process of the terminal user such as cell residence, access, reselection and handover will be shorter, and due to the Doppler frequency shift phenomenon The existence of , will cause the terminal UE connected to the Long Term Evolution (Long Term Evolution, LTE) network to receive a phase rotation of the data symbols, which will affect the accuracy of data demodulation and cause...

AI Technical Summary

Problems solved by technology

[0004] However, both of the above two technical solutions currently have relatively large disadvantages: the disadvantage of the first solution: since the mobile communication network corresponding to the high-speed traffic line mainly adopts the conventional macro cell coverage mode, the mobile communication network corresponding to the high-speed traffic line The users of the base station cell under the network coverage are not all real high-speed traffic line user groups, but also include resident users near the base station cell, which leads to the lack of pertinence of the KPI in the network management only for high-speed traffic line users; and Due to the real-time changes of the wireless network, the contingency is high, and it is difficult to find and solve the problem at one time during the drive test. high

The disadvantage of passive optimization: it is difficult for the complainant to locate the location and cause of the problem, and the data acquisition is poor; and also due to the accidental nature of the wireless network, it is difficult to find and solve the problem in the process of retesting after receiving the complaint, and the efficiency is low ;At the same time, solve the complaints after they have already occurred, the customer satisfaction is low, and the timeliness of problem data discovery and troubleshooting is poor

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