电信科学 ›› 2018, Vol. 34 ›› Issue (7): 128-134.doi: 10.11959/j.issn.1000-0801.2018212

• 研究与开发 • 上一篇    下一篇

基于高斯分布的基站天线最佳方向角定位算法

梁松柏1,陈锋2,宋海平3,李文生1   

  1. 1 中国联合网络通信有限公司河南省分公司,河南 郑州 450008
    2 中兴通讯股份有限公司河南分公司,河南 郑州 450003
    3 华为技术有限公司郑州咨询与系统集成部,河南 郑州 450018
  • 出版日期:2018-07-20 发布日期:2018-07-28

Optimal azimuth positioning algorithm for base station antenna based on Gaussian distribution

Songbai LIANG1,Feng CHEN2,Haiping SONG3,Wensheng LI1   

  1. 1 Henan Branch of China United Network Communications Co.,Ltd.,Zhengzhou 450008,China
    2 Henan Branch of ZTE Corporation,Zhengzhou 450003,China
    3 Zhengzhou C&SI,Huawei Technologies Co.,Ltd.,Zhengzhou 450018,China
  • Online:2018-07-20 Published:2018-07-28

摘要:

为提高天馈问题被发现的准确性和维护效率,提出了基于高斯分布的最佳方向角解决方案来诊断运营商天馈覆盖问题。首先计算 UE 上报的具有定位信息的每个 MR 采样点与基站之间的位置方向信息,然后按照位置方向的一定角度间隔逐个统计各区间的MR采样点占比,取MR采样点占比最大的角度区间为该扇区的、基于用户热点分布的最佳天线方向角,最后将该最佳方向角与后台天线基础数据库中基站方向角进行比对,发现天馈系统接反、天线覆盖方向不合理、后台天线数据库错误等一系列天馈相关问题。经验证,采用该算法发现天馈问题的成本、准确率和效率较现有方法有明显改善?。

关键词: 高斯分布, MR, 天线, 方向角, 定位算法

Abstract:

In order to improve the accuracy and efficiency of the discovery of the antenna-feeder problem,an optimal direction angle solution based on Gaussian distribution was proposed to diagnose the antenna-feeder coverage problems of operators.First of all,the location direction information between each MR sampling point reported by the UE and the base station was calculated,and then the proportion of MR sampling points in each interval was calculated,Based on the Gaussian distribution feature,the angle range with the largest proportion of MR sampling points was the appropriate azimuth,which was based on the user hotspot distribution of the sector.Finally,the date of optimal azimuth was compared with the base station azimuth in the background antenna database to detect antenna feeder problems,such as cross feeder,improper antenna coverage direction and incorrect background antenna database,and so on.The field verification shows that,the cost,accuracy and efficiency of the antenna-feeder problems are obviously improved compared with the existing methods.

Key words: Gaussian distribution, MR, antenna, azimuth, positioning algorithm

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