Abstract: With the great development of communication industry, the scale of mobile communication network becomes larger, and networks are increasingly complex. As the 2G network is being constantly optimized, the 3G network is becoming more mature, 4G network is under large-scale construction, it gradually or has become a challenge for mobile operators that how to accurately grasp real-time network status, how to perceive network performance from the view of users, how to evaluate the quality of network, restricts further optimization of mobile networks, and influence further improvement of user experience. Auxiliary test unit (ATU) is an indispensable tool for future performance testing and optimization of mobile network. Compared to traditional manual road test, ATU has fewer staff input, broader range of tests, shorter test cycles and other advantages; therefore the importance of ATU will highlight in the future mobile operator's daily network optimization. Mobile operators auto drive test (DT) platform provides abundant indicators currently, and it is an issue worthy of studying that how to select and classify these indicators in a quick and efficient evaluation of network quality. Using MATLAB, this paper conducts correlation analysis among KPIs, then accomplishes the classification for each indicator based on statistical principle, presents a mobile network indicator classification method, reduces the difficulty and improves the efficiency of the network quality analysis.

Key words: mobile communication, network quality, KPI, indicator classification