Abstract
At present, LTE network quality analysis is mainly based on Drive Test (DT) and Call Quality Test (CQT). Both methods require a large number of professional network optimization engineers and testing equipment. The testing methods cost a lot of time and money, and they cannot diagnose the causes of LTE network quality difference in time, which seriously affects customer perception. In this paper, a method of LTE network quality analysis based on Measurement Report (MR) data and XGBoost classification algorithm is proposed to quickly diagnose the cause of poor quality network. This method can effectively and comprehensively reflect customer perception. It can provide useful information for network optimization. It greatly improves the efficiency of network optimization engineers, and reduces a large number of labor costs.
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