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首页> 外文期刊>Simulation modelling practice and theory: International journal of the Federation of European Simulation Societies >A subscriber classification approach for mobile cellular networks
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A subscriber classification approach for mobile cellular networks

机译：移动蜂窝网络的用户分类方法

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摘要

The classification of subscriber types in mobile cellular networks is valuable for network service providers since it provides a mechanism to plan network services by better understanding subscriber behaviour in a network. Mobile networks contain vast repositories of data that store valuable information regarding subscriber behaviour. In this paper, a new approach for subscriber classification in mobile cellular networks is proposed. The proposed approach considers network traffic generated from a mobile cellular network operator in South Africa. The proposed approach makes use of a difference histogram approach for feature extraction and a fuzzy c-means clustering algorithm to classify traffic data into subscriber classes. To validate the proposed approach, a comparative analysis of two different multi-resolution feature extraction approaches, the empirical mode decomposition (EMD) approach and the discrete wavelet packet transform (DWPT) are compared with results obtained with the difference histogram (DH) approach. It is shown that the difference histogram provides better clustering results when compared to the two multi-resolution approaches demonstrating the potential of the difference histogram approach.
机译：移动蜂窝网络中用户类型的分类对于网络服务提供商来说很有价值，因为它提供了一种通过更好地了解网络中用户行为来规划网络服务的机制。移动网络包含大量数据存储库，这些数据存储有关订户行为的宝贵信息。本文提出了一种新的移动蜂窝网络中用户分类的方法。所提出的方法考虑了南非移动蜂窝网络运营商产生的网络流量。所提出的方法利用差异直方图方法进行特征提取，并使用模糊c均值聚类算法将交通数据分类为订户类别。为了验证所提出的方法，将两种不同的多分辨率特征提取方法，经验模式分解（EMD）方法和离散小波包变换（DWPT）进行比较分析，并与差异直方图（DH）方法获得的结果进行比较。结果表明，与两种多分辨率方法相比，差异直方图提供了更好的聚类结果，表明了差异直方图方法的潜力。

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