基于DBSCAN的基站定位算法

Base Station Location Algorithm Based on DBSCAN

随着无线移动设备的普及,基于用户位置的服务给人们的生活带来了极大的便利,服务提供商如何准确定位用户位置成为研究热点。在定位过程中,由于基站数据陈旧、信息缺失、位置偏差大等因素,导致了定位精度下降,针对上述问题,论文提出一种基于DBSCAN的基站定位算法,对一定区域内的用户位置进行密度聚类,对聚类结果分别计算区域权重,结合K-means得到基站位置。实验结果表明,定位准确度在83.52%以上。

With the popularity of wireless mobile devices,services based on user location have brought great convenience to people’s lives. How to accurately locate users’ locations has become a research hotspot. In the positioning process,due to the obsolete data of the base station,the lack of information,and the large position deviation,the positioning accuracy is degraded. In view of the above problems,this paper proposes a base station positioning algorithm based on DBSCAN to density the user location in a certain area. The regional weights for the clustering results are calculated,and the base station location is obtained by combining K-means. Experimental results show that the positioning accuracy is above 83.52%.