移动通信网络KPI指标分类方法研究

随着通信技术的发展，移动通信网络规模越来越大，网络越来越复杂，2G网络的不断优化精细，3G网络的日臻成熟以及4G网络的大规模商用，如何准确、实时地掌握网络的运行情况，如何从用户的角度感知网络性能，如何评价网络的质量等问题正逐渐或者已经成为移动运营商的挑战，制约移动网络的进一步优化，影响用户体检的进一步提高。自动路测是未来移动网络性能检测和优化中不可或缺的重要工具。相比于传统人工路测，自动路测具有更少的人员投入、更广的测试范围、更短的测试周期等优势，在运营商的日常网络优化中的重要性凸显。当前移动运营商的自动路测平台有丰富的测试指标，如何选取和分类这些指标以快速评估网络质量是一个值得研究的问题。文章利用MATLAB分析KPI指标之间的相关性，并通过统计学原理对各指标进行了分类，给出了一种移动网络KPI指标分类方法，降低了网络质量分析的难度，提高了网络质量分析效率。

The Method of KPI Classiifcation of Mobile Communication Network

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＆#39;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 efifcient evaluation of network quality. Using MATLAB, this paper conducts correlation analysis among KPIs, then accomplishes the classiifcation for each indicator based on statistical principle, presents a mobile network indicator classiifcation method, reduces the dififculty and improves the efifciency of the network quality analysis.