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1. 中国移动通信集团设计院有限公司重庆分公司,重庆 401121
2. 中国移动通信集团云南有限公司,云南 昆明 650228
[ "刘璐(1986- ),男,中国移动通信集团设计院有限公司重庆分公司工程师、高级咨询设计师,主要研究方向为无线网络智能优化" ]
[ "陈睿杰(1987- ),男,中国移动通信集团云南有限公司工程师,主要研究方向为大数据分析、AI、智慧运维" ]
[ "李嘉(1989- ),男,现就职于中国移动通信集团云南有限公司,主要研究方向为大数据分析、AI、智慧运维等" ]
网络出版日期:2022-02,
纸质出版日期:2022-02-20
移动端阅览
刘璐, 陈睿杰, 李嘉. 基于MDT重叠覆盖度数据的KNN-DBSCAN参数自适应调优研究[J]. 电信科学, 2022,38(2):119-129.
Lu LIU, Ruijie CHEN, Jia LI. Research on adaptive optimization of KNN-DBSCAN parameters based on MDT overlapping coverage data[J]. Telecommunications science, 2022, 38(2): 119-129.
刘璐, 陈睿杰, 李嘉. 基于MDT重叠覆盖度数据的KNN-DBSCAN参数自适应调优研究[J]. 电信科学, 2022,38(2):119-129. DOI: 10.11959/j.issn.1000-0801.2022010.
Lu LIU, Ruijie CHEN, Jia LI. Research on adaptive optimization of KNN-DBSCAN parameters based on MDT overlapping coverage data[J]. Telecommunications science, 2022, 38(2): 119-129. DOI: 10.11959/j.issn.1000-0801.2022010.
传统网络优化中路测工作存在难以全量测试道路及楼宇、测试工作量大、工作效率低、周期长、受人为因素影响等显性缺点,无法动态关注每个区域网络质量情况,且常规测量报告(measurement report,MR)数据不具备定位信息,无法精确定位如重叠覆盖度问题发生位置。基于最小化路测(minimization drive test, MDT)精准定位系统通过采集底层基站 MDT 数据,并根据重叠覆盖度算法输出高重叠覆盖度栅格,再通过自适应K最近邻-具有噪声的基于密度的聚类方法(K-nearest neighbor density-based spatial clustering of applica-tions with noise,KNN-DBSCAN)联合算法解决了DBSCAN算法对参数设置敏感性问题,并对问题栅格进行非监督聚类,收敛问题连片区域,通过小区采样贡献度进行栅格区域映射,最终达到精准调整全局最高优先级(TOP)小区,降低小区高重叠覆盖度的目的。
In the traditional network optimization
the drive test (DT) work has obvious disadvantages
such as difficult to fully test roads and buildings
large test workload
low work efficiency
long cycle
affected by human factors
unable to dynamically pay attention to the network quality of each area
and the conventional measurement report (MR) data does not have positioning information
so it is impossible to accurately locate the location where the overlapping coverage problem occured.Based on minimization drive test (MDT)
the precision positioning system collected the MDT data of the underlying base station and outputted the grid with high overlapping coverage according to the overlapping coverage algorithm.Then
the sensitivity of DBSCAN algorithm to parameter setting was solved through the adaptive K-nearest neighbor density-based spatial clustering of applications with noise (KNN-DBSCAN)joint algorithm.The problem grid was unsupervised clustered
the problem contiguous area was converged
and the grid area was mapped through the cell sampling contribution.Finally
the global top cell was accurately adjusted to optimize the high overlap coverage.
谭钰山 , 周文金 , 何延 . 基于MDT数据的重叠覆盖优化思路及实践 [J ] . 通讯世界 , 2019 , 26 ( 12 ): 6 - 7 .
TAN Y S , ZHOU W J , HE Y . Overlapping coverage optimization idea and practice based on MDT data [J ] . Telecom World , 2019 , 26 ( 12 ): 6 - 7 .
张吉 , 赵夙 , 朱晓荣 . 基于大数据挖掘的 LTE 网络重叠覆盖优化方法 [J ] . 南京邮电大学学报(自然科学版) , 2020 , 40 ( 6 ): 92 - 99 .
ZHANG J , ZHAO S , ZHU X R . Optimization method for overlapping coverage of LTE networks based on big data mining [J ] . Journal of Nanjing University of Posts and Telecommunications (Natural Science Edition) , 2020 , 40 ( 6 ): 92 - 99 .
谷欣杏 . LTE 网络覆盖优化及无线定位优化算法的研究 [D ] . 北京:北京邮电大学 , 2019 .
GU X X . Research on LTE network coverage optimization and wireless positioning algorithm [D ] . Beijing:Beijing University of Posts and Telecommunications , 2019 .
宋金玉 , 郭一平 , 王斌 . DBSCAN 聚类算法的参数配置方法研究 [J ] . 计算机技术与发展 , 2019 , 29 ( 5 ): 44 - 48 .
SONG J Y , GUO Y P , WANG B . Research on parameter configuration method of DBSCAN clustering algorithm [J ] . Computer Technology and Development , 2019 , 29 ( 5 ): 44 - 48 .
赵文 , 夏桂书 , 苟智坚 , 等 . 一种改进的 DBSCAN 算法 [J ] . 四川师范大学学报(自然科学版) , 2013 , 36 ( 2 ): 312 - 316 .
ZHAO W , XIA G S , GOU Z J , et al . An improved DBSCAN algorithm [J ] . Journal of Sichuan Normal University (Natural Science) , 2013 , 36 ( 2 ): 312 - 316 .
何正风 . MATLAB 在数学方面的应用 [M ] . 北京 : 清华大学出版社 , 2012 .
HE Z F . Application of MATLAB in mathematics [M ] . Beijing : Tsinghua University Press , 2012 .
李文杰 , 闫世强 , 蒋莹 , 等 . 自适应确定 DBSCAN 算法参数的算法研究 [J ] . 计算机工程与应用 , 2019 , 55 ( 5 ): 1 - 7 , 148 .
LI W J , YAN S Q , JIANG Y , et al . Research on method of self-adaptive determination of DBSCAN algorithm parameters [J ] . Computer Engineering and Applications , 2019 , 55 ( 5 ): 1 - 7 , 148 .
王紫薇 , 徐凯 , 侯益明 . 基于不同距离公式的KNN算法对鸢尾花的分类 [J ] . 无线互联科技 , 2021 , 18 ( 13 ): 105 - 106 .
WANG Z W , XU K , HOU Y M . Classification of iris based on KNN algorithm with different distance formulas [J ] . Wireless Internet Technology , 2021 , 18 ( 13 ): 105 - 106 .
周红芳 , 王鹏 . DBSCAN 算法中参数自适应确定方法的研究 [J ] . 西安理工大学学报 , 2012 , 28 ( 3 ): 289 - 292 .
ZHOU H F , WANG P . Research on adaptive parameters determination in DBSCAN algorithm [J ] . Journal of Xi’an University of Technology , 2012 , 28 ( 3 ): 289 - 292 .
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