Research on adaptive optimization of KNN-DBSCAN parameters based on MDT overlapping coverage data

Lu LIU; Ruijie CHEN; Jia LI

doi:10.11959/j.issn.1000-0801.2022010

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Research on adaptive optimization of KNN-DBSCAN parameters based on MDT overlapping coverage data

Research and Development | 更新时间：2024-06-05

- Research on adaptive optimization of KNN-DBSCAN parameters based on MDT overlapping coverage data
- Telecommunications Science Vol. 38, Issue 2, Pages: 119-129(2022)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2022010
  CLC： TN929.5
- Published Online：2022-02，
  
  Published：20 February 2022
- 稿件说明：
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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：

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.

摘要

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。

Abstract

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.

关键词

Keywords

references

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