基于改进k-均值聚类算法的LTE基站需求选点方法

Method for selecting demand points of LTE base station based on improved k-means clustering algorithm

针对目前LTE基站需求阶段选点由于多部门、多类型来源导致在同一个相近位置附近存在重复上报的问题,为了提高无线基站规划的建设效率,通过对普通k-均值聚类算法中初始k值、聚类中心、离散点处理这几个关键点进行改进,进而提出一种全新的无线基站需求选点方法。该方法已嵌入目前已投入使用的无线规划设计审核平台中,在需求阶段中得到了很好的应用。

Recently,there are repeating report data on one point nearby in the demand stage of LTE base station because of the data coming from several department with multiple types. In order to improve the construction efficiency of wireless base station planning,a new method of selecting the demand of wireless base station which based on improved k-means clustering algorithm was proposed,compared to ordinary one including some key points such as initial k value,clustering center,discrete point. Finally,this method already had been used well in Audit IT platform for wireless planning and designing which had been put into use.