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DOI: 10.14569/IJACSA.2013.040333

Genetic algorithms to optimize base station sitting in WCDMA networks

Author 1: Najat Erradi
Author 2: Noura Aknin
Author 3: Fadoua Thami Alami
Author 4: Ahmed El Moussaoui

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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 3, 2013.

  • Abstract and Keywords
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Abstract: In UMTS network, radio planning cannot only be based on signal predictions, but it must also consider the traffic distribution, the power control mechanism as well as the power limits and the signal quality constraints. The present work aims to optimize the number of base stations used in the WCDMA radio network. In this paper, we propose a mathematical programming model for optimizing the base station locations considered for the uplink (mobile to BS) direction, and which considers the typical power control mechanism of WCDMA. The two contrasting objectives of the optimization process are the traffic coverage maximization and the installation costs minimization. A mimetic algorithm (AM) (genetic algorithm+ a local search) is proposed to find good approximate solutions of this NP hard problem. The Numerical results are obtained for reels instances, and generated by using classical propagation models.

Keywords: Ukumura-Hata model; UMTS; W-CDMA; Genetic Algorithms.

Najat Erradi, Noura Aknin, Fadoua Thami Alami and Ahmed El Moussaoui, “Genetic algorithms to optimize base station sitting in WCDMA networks” International Journal of Advanced Computer Science and Applications(IJACSA), 4(3), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040333

@article{Erradi2013,
title = {Genetic algorithms to optimize base station sitting in WCDMA networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2013.040333},
url = {http://dx.doi.org/10.14569/IJACSA.2013.040333},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {3},
author = {Najat Erradi and Noura Aknin and Fadoua Thami Alami and Ahmed El Moussaoui}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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