大数据分析与网络弱覆盖优化方案

Large data analysis and poor coverage discovery

网络弱覆盖严重影响用户感知,是运营商最为关注并需首要解决的问题之一。网络弱覆盖的发现来源主要有路测、用户投诉等,近年来,随着大数据采集与分析能力的提升,也成为了弱覆盖发现的重要手段之一。本文以某密集城区为例,介绍从基于Hadoop的大数据解析、大数据定位、到网络弱覆盖发现与优化建议的整个流程,给实际网络规划优化工作提供经验。

Because poor coverage is a serious impact on user perception, it is one of the most important issues for operators and one of the most important issues to be solved. In the past, the main sources of poor coverage were road test, user complaint and so on. In recent years, with the enhancement of large data acquisition and analysis ability, MR data analysis has also become one of the most important means of poor coverage discovery. Taking a dense urban area as an example, this paper introduces the whole process of large data parsing, large data location, poor coverage discovery and optimization suggestions. The method of this paper provides experience for the actual network planning optimization.