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Erschienen in:
2008 | OriginalPaper | Buchkapitel
The Use of Semi-parametric Methods for Feature Extraction in Mobile Cellular Networks
verfasst von : A. M. Kurien, B. J Van Wyk, Y. Hamam, Jaco Jordaan
Erschienen in: Intelligent Data Engineering and Automated Learning – IDEAL 2008
Verlag: Springer Berlin Heidelberg
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By 2006, the number of mobile subscribers in Africa outnumbered that of fixed line subscribers with nearly 200 million mobile subscribers across the continent [1][2]. By the end of 2007, it was estimated that the number of mobile subscribers would exceed 278 million subscribers [2]. Mobile Telephony has been viewed as a critical enabling technology that is capable of boosting local economies across Africa due to the ease of roll out of wireless technologies in comparison to fixed line networks. With the boom in wireless networks across Africa, a growing demand to effectively predict the rate of growth in demand for capacity in various sectors of the network has risen with cellular network operators. This paper looks at using
Spectral Analysis
techniques for the extraction of features from cellular network traffic data that could be linked to subscriber behavior. This could then in turn be used to determine capacity requirements within the network.