摘要
为了降低网优的工作中人工测试的工作量、降本增效,通过采用大数据分析的方法,对用户手机采集上报的MR数据进行分析,研究了不同道路场景的MR定位优化算法,并提出了道路栅格化、数据清洗、栅格汇聚及道路覆盖GIS呈现、自动发现道路典型覆盖问题的虚拟化路测实现方案。经过人工路测与虚拟化路测对比验证,证实了虚拟化路测的可行性和准确性。
In order to reduce the workload of artificial tests, decrease the cost and increase efficacy in the network optimization, the big data analysis method was used to analyze the MR data collected and reported by users' terminals. The MR localization optimization algorithms suitable tbr different scenarios were investigated. The implementation scheme on the virtual drive tests of the grid road, data cleaning, grid aggregation, road coverage GIS display and automatic discovery of typical road coverage was put forward. The virtual drive test is compared with the artificial drive test. Results validate the feasibility and accuracy of the virtual drive test.
出处
《移动通信》
2017年第12期1-5,共5页
Mobile Communications
关键词
MR
大数据
用户识别
虚拟化路测
MR big data user identification virtual drive test