基于基站流量数据的用户上网时间分析研究

摘要

In order to effectively solve the problem of mobile user’s personalized demand in different time and location, this paper analyzed the characteristics of each base station traffic data of each hour, using k-means clustering algorithm to identify how busy each base station is, and analyzing mobile users time and location demand of data business to guide operators network planning scheme was proposed. Experiments verified the effectiveness of the method, and found that identifying how busy a base station is using K-means clustering analysis algorithm is of high scalability.%为了有效解决移动用户在不同时间、不同位置对网络的个性化需求问题，通过分析每一个基站每小时的流量数据的特点，采用K-means聚类分析算法来识别每一个基站的繁忙程度，提出了分析移动用户对数据业务的时间与空间需求指导运营商网络规划的方案。经过实验验证了该方案的有效性，并发现基于K-means聚类分析算法识别基站的繁忙程度具有较高的扩展性。