Abstract
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.
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References
ICT in Africa: Forging a Competitive Edge, ITU Connect Africa (October 2007), http://www.itu.int/ITU-D/connet/africa/2007/media/kit/africa_ict.html
Telecommunication/ICT Markets and Trends in Africa 2007, Connect Africa Summit, Kigali, Rwanda (October 2007), http://www.itu.int
Mbarika, V.W.A., Mbarika, I.: Africa Calling [Africa Wireless Connection]. IEEE Spectrum 43(5), 56–60 (2006)
Tutschku, K.: Demand-Based Radio Network Planning of Cellular Mobile Communication Systems. In: IEEE Conference on Computer Communication (INFOCOM), April 1998, (1), pp. 1054–1061 (1998)
Tutschku, K., Leibnitz, K., Tran-Gia, P.: ICEPT- An Integrated Cellular Network Planning Tool. In: Vehicular Technology Conference (VTC), Phoenix, USA, May 1997, pp. 765–769 (1997)
Tutschku, K., Tran-Gia, P.: Spatial Traffic Estimation and Characterization for Mobile Communication Network Design. IEEE Journal on Selected Areas in Communications 16(5), 804–811 (1998)
Gawrysiak, P., Okoniewski, M.: Applying Data Mining Methods for Cellular Radio Network Planning. In: Proceedings of the International Intelligent Information Systems Conference, Advances in Soft Computing Journal. Springer, Heidelberg (2000)
Khedher, H., Valois, F., Tabbane, S.: Traffic Characterization for Mobile Networks. In: 56th IEEE Vehicular Technology Conference (VTC), September 2002, vol. 3, pp. 1485–1489 (2002)
Camilleri, M.: Forecasting Using Non-Linear Techniques in Time Series Analysis: An Overview of Techniques and Main Issues. In: Computer Science Annual Research Workshop (CSAW 2004), September 2004, pp. 19–28 (2004)
Zivanovic, R.: Analysis of Recorded Transients on 765kV Lines with Shunt Reactors. In: Proc. Power Tech 2005 Conference, St. Petersburg, Russia (2005)
Zivanovic, R., Schegner, P., Seifert, O., Pilz, G.: Identification of the Resonant-Grounded System Parameters by Evaluating Fault Measurement Records. IEEE Transactions on Power Delivery 19(3), 1085–1090 (2004)
Draper, N., Smith, H.: Applied Regression Analysis, 2nd edn. John Wiley & Sons, Chichester (1981)
Jordaan, J.A., Zivanovic, R.: Time-varying Phasor Estimation in Power Systems by Using a Non-quadratic Criterium. Transactions of the South African Institute of Electrical Engineers (SAIEE), 95(1), 35–41 (March 2004) ERRATA: 94(3), 171–172 (September 2004)
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Kurien, A.M., Van Wyk, B.J., Hamam, Y., Jordaan, J. (2008). The Use of Semi-parametric Methods for Feature Extraction in Mobile Cellular Networks. In: Fyfe, C., Kim, D., Lee, SY., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2008. IDEAL 2008. Lecture Notes in Computer Science, vol 5326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88906-9_37
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DOI: https://doi.org/10.1007/978-3-540-88906-9_37
Publisher Name: Springer, Berlin, Heidelberg
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