摘要
现有对无线覆盖问题原因定界的DT、CQT、扫频手段,费时费力样本点不足,难以反映网络覆盖的整体情况,且仅凭经验和直觉输出优化方案,效率低下。通过对MR数据TA和AOA定位的深入研究,提出了一种基于模式识别的问题原因定界及优化方法。通过MR数据TA和AOA定位用户,建立MR覆盖多维矩阵并与传播模型参考系比对,基于模式识别算法,自动识别出导致覆盖问题的原因,并针对不同类别的覆盖问题给出不同的优化方案。该项研究在全省4G驻留比由96.6%提升到98.4%,4G网络综合覆盖率由90.0%提升到95.1%的前提下,全年节约非主干道深度覆盖测试成本576万元,节约了测试成本,提高了工作效率。LTE投诉万户比从2.3下降到1.2,提升了公司数据业务品牌价值。
The existing methods of DT,CQT and frequency sweeping for delimitation of the causes of wireless coverage problems are time-consuming and laborious and lack of sample points,which are difficult to reflect the overall situation of network coverage.Moreover,they are only based on the empirical and intuitive output optimization scheme,which is inefficient.Based on the deep research of the location of MR data TA and AOA,a method of problem cause demarcation and optimization based on pattern recognition is proposed.By using MR data TA and AOA to locate users,the multi-dimensional matrix of MR coverage was established and compared with the reference frame of the propagation model.Based on the pattern recognition algorithm,the causes of coverage problems were automatically identified,and different optimization schemes were proposed for different types of coverage problems.In this study,on the premise that the 4G resident ratio in the whole province increased from 96.6%to 98.4%and the comprehensive coverage rate of 4G network increased from 90.0%to 95.1%,the test cost of non-trunk road depth coverage was saved by 5.76 million yuan in the whole year,which saved the test cost and improved the work efficiency.LTE complaints per 10,000 households fell from 2.3 to 1.2,boosting the brand value of the company’s data business.
作者
周巍
Zhou Wei(Hubei Network Excellence Center of China Mobile Communication Group Co.,Ltd Hubei Wuhan 430023)
出处
《长江信息通信》
2021年第8期172-175,共4页
Changjiang Information & Communications
