基于聚类算法的5G网络覆盖问题智能定位

Intelligent Location of 5G Network Coverage Problem Based on Clustering Algorithm

基于聚类算法的5G网络覆盖问题智能定位,通过对现有网络运行数据的分析,自动、快速、准确地定位网络覆盖问题,以确保用户连续、高质量的进行通信业务。引入动态AP聚类和DBSCAN聚类算法,分析5G网络中的MDT数据,自动定位覆盖问题并实现地理化聚集,降低人工成本,提升网络效率。

Coverage problem location based on clustering algorithm can locate the network defaults automatically,promptly and correctly by processing the network monitoring statistics,so as to ensure the continuous and high-quality communication service of users.The dynamic AP clustering and DBSCAN clustering algorithm are introduced to analyze the MDT data in 5G network,automatically locate the coverage problem and realize geographic aggregation,reduce the labor cost and improve the network efficiency.