Abstract
Frequency assignment is a well-known problem in Operations Research for which different mathematical models exist depending on the application specific conditions. However, most of these models are far from considering actual technologies currently deployed in GSM networks (e.g. frequency hopping). These technologies allow the network capacity to be actually increased to some extent by avoiding the interferences provoked by channel reuse due to the limited available radio spectrum, thus improving the Quality of Service (QoS) for subscribers and an income for the operators as well. Therefore, the automatic generation of frequency plans in real GSM networks is of great importance for present GSM operators. This is known as the Automatic Frequency Planning (AFP) problem. In this paper, we focus on solving this problem for a realistic-sized, real-world GSM network by using Evolutionary Algorithms (EAs). To be precise, we have developed a (1,λ) EA for which very specialized operators have been proposed and analyzed. Results show that this algorithmic approach is able to compute accurate frequency plans for real-world instances.
This work has been partially funded by the Ministry of Science and Technology and FEDER under contract TIN2005-08818-C04-01 (the OPLINK project).
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References
Mouly, M., Paulet, M.B.: The GSM System for Mobile Communications. Mouly et Paulet, Palaiseau (1992)
Rapeli, J.: UMTS: Targets, system concept, and standardization in a global framework. IEEE Personal Communications 2, 30–37 (1995)
Granbohm, H., Wiklund, J.: GPRS – general packet radio service. Ericsson Review (1999)
Furuskar, A., Naslund, J., Olofsson, H.: EDGE – enhanced data rates for GSM and TDMA/136 evolution. Ericsson Review (1999)
Aardal, K.I., van Hoesen, S.P.M., Koster, A.M.C.A., Mannino, C., Sassano, A.: Models and solution techniques for frequency assignment problems. 4OR 1, 261–317 (2003)
FAP Web: (http://fap.zib.de/)
Kotrotsos, S., Kotsakis, G., Demestichas, P., Tzifa, E., Demesticha, V., Anagnostou, M.: Formulation and computationally efficient algorithms for an interference-oriented version of the frequency assignment problem. Wireless Personal Communications 18, 289–317 (2001)
Eisenblätter, A.: Frequency Assignment in GSM Networks: Models, Heuristics, and Lower Bounds. PhD thesis, Technische Universität Berlin (2001)
Hale, W.K.: Frequency assignment: Theory and applications. Proceedings of the IEEE 68, 1497–1514 (1980)
Blum, C., Roli, A.: Metaheuristics in Combinatorial Optimization: Overview and Conceptual Comparison. ACM Computing Surveys 35, 268–308 (2003)
Glover, F.W., Kochenberger, G.A.: Handbook of Metaheuristics. Kluwer, Dordrecht (2003)
Bäck, T.: Evolutionary Algorithms: Theory and Practice. Oxford University Press, New York (1996)
Dorne, R., Hao, J.K.: An evolutionary approach for frequency assignment in cellular radio networks. In: Proc. of the IEEE Int. Conf. on Evolutionary Computation. pp. 539–544 (1995)
Smith, D.H., Allen, S.M., Hurley, S.: Characteristics of good meta-heuristics algorithms for the frequency assignment problem. Annals of Operations Research 107, 285–301 (2001)
Schwefel, H.P.: Numerical Optimization of Computer Models. Wiley, Chichester, UK (1981)
Mishra, A.R.: Radio Network Planning and Optimisation. In: Fundamentals of Cellular Network Planning and Optimisation: 2G/2.5G/3G ... Evolution to 4G, pp. 21–54. Wiley, Chichester (2004)
Kampstra, P., van der Mei, R.D., Eiben, A.E.: Evolutionary computing in telecommunication network design: A survey. In Revision (2006)
Vidyarthi, G., Ngom, A., Stojmenović, I.: A hybrid channel assignment approach using an efficient evolutionary strategy in wireless mobile networks. IEEE Transactions on Vehicular Technology 54, 1887–1895 (2005)
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Luna, F., Alba, E., Nebro, A.J., Pedraza, S. (2007). Evolutionary Algorithms for Real-World Instances of the Automatic Frequency Planning Problem in GSM Networks. In: Cotta, C., van Hemert, J. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2007. Lecture Notes in Computer Science, vol 4446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71615-0_10
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DOI: https://doi.org/10.1007/978-3-540-71615-0_10
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