Abstract
The planning and optimization of WCDMA (wideband code-division multiple access)radio network issues remain vital, and are carried out using static snapshot-based simulation. To improve the accuracy of the static simulation, link-level performance factors, such as the impact of power control, pilot power and soft handover, have to be taken into account. These factors have not been investigated together in the previous works. In this paper, we give a brief introduction to our programming models that take these characteristics into account, and present optimisation strategies based on three major Metaheuristics; genetic algorithms (GA), simulated annealing (SA) and tabu search (TS). Extensive experimental results are provided and the performance of different heuristic algorithms is compared.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Laiho, J., Wacker, A., Novosad, T.: “Radio Network Planning and Optimization for UMTS (, 2nd edn. John Wiley, New York, NY (2005)
Amaldi, E., Capone, A., Malucelli, F.: “Planning UMTS Base Station Location: Optimization Models With Power Control and Algorithms”. IEEE Trans. Wireless Communications 25, 939–952 (2003)
Mathar, R., Schmeink, M.: Optimal Base Station Positioning and Channel Assignment for 3G Mobile Networks by Integer Programming. Annals of Operations Research, pp. 225-236 (2001)
Eisenblätter, A., Fugenschuh, A.: et al, “Integer Programming Methods for UMTS Radio Network Planning”, Proc. of WiOpt’04, Cambridge, UK (2004)
Akl, R.G., Hegde, M.V. et al.: Multicell CDMA Network Design. IEEE Trans. Veh. Technol. 503, 711–722 (2001)
Lee, C.Y., Kang, H.G.: “Cell Planning with Capacity Expansion in Mobile Communications: A Tabu Search Approach”. IEEE Trans. Veh. Technol. 495, 1678–1691 (2000)
Hurley, S.: “Planning Effective Cellular Mobile Radio Networks”. IEEE Trans. Veh. Technol. 51(2), 243–253 (2002)
Kocsis, L.: 3G Base Station Positioning Using Simulated Annealing’. Proc. of IEEE PIMRC’02 1, 330–334 (2002)
Demirkol, I., Ersoy, C., Caglayan, M.U., Delic, H.: Location Area Planning in Cellular Networks Using Simulated Annealing, Proc. of IEEE INFOCOM’01, Anchorage, April (2001)
Farkas, L., Laki, I., Nagy, L.: Base Station Position Optimization in Microcells Using Genetic Algorithms, Proc. of IEEE ICT’01, Bucharest, Romania, (June 2001)
Raisanen, L., Whitaker, R.M.: “Comparison and Evaluation of Multiple Objective Genetic Algorithms for the Antenna Placement Problem”, Mobile Networks and Applications, No. Mobile Networks and Applications 10, 79–88 (2005)
Jamaa, S.B., Altman, Z. et al.: Manual and Automatic Design for UMTS Networks. Mobile Networks and Applications 9, 619–626 (2004)
Laarhoven, V.: P. J. M. and E. H. Aarts. “Simulate Annealing: Theory and Applications”. Dordrecht, Holland: D. Reidel (1987)
Reeves, C.R., Rowe, J.E.: Genetic Algorithms-Principles and Perspectives. Kluwer Academic Publishers, Boston, MA (2004)
Alp, O., Drezner, Z., Erkut, E.: An Efficient Genetic Algorithm for the p-Median Problem. Annals of Operations Research 122(1-4), 21–42 (2003)
Chu, P.C., Beasley, J.E.: A Genetic Algorithm for the Set Covering Problem. European Journal of Operational Research 94, 392–404 (1996)
Chan, K.Y., Aydin, M.E., Fogarty, T.C.: Parameterisation of Mutation in Evolutionary Algorithms Using the Estimated Main Effect of Genes, Proc. of the IEEE International Congress on Evolutionary Computation, 19-23 Jun. 2004, Portland, Oregon, USA, pp (1972)-1979
Kirkpatrick, S., Gelatt Jr, C.D., Vecchi, M.P.: Optimization by Simulated Annealing. Science 220(4598), 671–680 (1983)
Aydin, M.E., Fogarty, T.C.: “A Distributed Evolutionary Simulated Annealing for Combinatorial Optimisation Problems”. Journal of Heuristics 10(3), 269–292 (2004)
Yigit, V., Aydin, M.E, Turkbey, O.: Solving Large Scale Uncapacitated Facility Location Problems with Evolutionary Simulated Annealing. International Journal of Production Research, 44(22), pp. 4773-4791
Glover, F., Laguna, M.: “Tabu search”, Hingham, MA. Kluwer Academic Publishers, Boston, MA (1997)
Glover, F.: Parametric Tabu-search for Mixed Integer Programs’. Computers & Operations Research 33(9), 2449–2494 (2006)
Sun, M.: Solving the Uncapacitated Facility Location Problem Using Tabu Search. Computers & Operations Research 33(9), 2563–2589 (2006)
Yang, J., Aydin, M. E., Zhang J.,and Maple, C.:UMTS Radio Network Planning: a Mathematical Model and Heuristic Optimisation Algorithms, accepted for publication in IET Communications, 2007
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Aydin, M.E., Yang, J., Zhang, J. (2007). A Comparative Investigation on Heuristic Optimization of WCDMA Radio Networks. In: Giacobini, M. (eds) Applications of Evolutionary Computing. EvoWorkshops 2007. Lecture Notes in Computer Science, vol 4448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71805-5_12
Download citation
DOI: https://doi.org/10.1007/978-3-540-71805-5_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71804-8
Online ISBN: 978-3-540-71805-5
eBook Packages: Computer ScienceComputer Science (R0)