Data Analysis of Measurement Report and Diagnosis of Mobile Network Malfunction Based on K-Means Algorithm
With the rapid development of mobile networks, the number of mobile subscriptions has continued to increase. To efficiently assign mobile network resources, the network operator needs to process and analyze information and statistics about each base station and the traffic that passes through it. This paper presents an application of data analytic by focusing on processing and analyzing datasets from MR (measurement report) data form the actual mobile network. An analysis method based on k-means algorithm for the main service cell uplink SINR (Signal to Interference plus Noise Ratio) analysis of the base station is presented. The analysis of MR data includes data cleaning and K-means algorithm. The purpose of data cleaning is to remove duplicate information, correct existing errors and provide the data consistency. The K-means is an algorithm used for clustering the main service cell uplink SINR in MR data. Finally, through the simulation results, The reason for the malfunction of the base station is obtained. The result can provide support for network optimization and maintenance.
KeywordsMeasurement report Uplink SINR Data cleaning Clustering K-means Malfunction analysis
This work was funded by National Science and Technology Major Project No. 2016ZX03001009-003 and 2017 Beijing University of Posts and Telecommunications youth research and innovation project. The authors would like to thank our lab for providing the network optimization software, from which the map information was obtained.
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