Applying Ant Colony Optimization to the Problem of Cell Planning in Mobile Telephone System Radio Network

Authors

  • Osmar Viera Carcache Universidad Técnica Estatal de Quevedo
  • Leonardo Vinces Llaguno Universidad Técnica Estatal de Quevedo, nstituto Tecnológico Superior “Honorable Consejo Provincial de Pichincha”
  • Kenya Guerrero Goyes Universidad Técnica Estatal de Quevedo
  • Fabricio Marcillo Vera Universidad Técnica Estatal de Quevedo

DOI:

https://doi.org/10.29019/enfoqueute.v8n2.156

Keywords:

cell planning problem, ant colony optimization, telecommunications, combinatorial optimization, meta-heuristics

Abstract

This paper presents a computational proposal for the solution of the Cell Planning Problem. The importance of this problem in the area of Telecommunications imposes it as a reference in the search for new methods of optimization. Due to the complexity of the problem, this work uses a discrete relaxation and proposes a mathematical model for the application of the Meta-heuristic Ant Colony Optimization (ACO). For the analysis of the results, 5 instances of the problem of different sizes were selected and the Ants System (AS) algorithm was applied. The results show that the proposal efficiently explores the search space, finding the optimal solution for each instance with a relatively low computational cost. These results are compared with 3 evolutionary alternatives of international reference that have been applied to the same study instances, showing a significant improvement by our proposal.

Metrics

Downloads

Download data is not yet available.

References

Alba, E., Molina, G., & Nebro, A. J. (2011). Disposición óptima de antenas usando CHC multiobjetivo.
Ayuso, R., Ceña, B., Fernández, M., Millán, B., & Saturnina Torre, M. (1999). Comunicaciones móviles GSM. Fundación Airtel.
Bäck, T., Hammel, U., & Schwefel, H. (1997). Evolutionary Computation: Comments on the History and Current State. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 3-17.
Bonabeau, E. (1999). Swarm Intelligence: From natural to artificial systems. Oxford University Press.
Calégari, P., Guidec, F., Kuonen, P., & Kobler, D. (1997). Parallel Island-Based Genetic Algorithm for Radio Network Design. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 86-90.
Cano, J. R., Herrera, F., & Lozano, M. (2003). Using Evolutionary Algorithms as Instance Selection for Data Reduction in KDD: An Experimental Study. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 561-575.
Engelbrecht, A. P. (2006). Fundamentals of Computational Swarm Intelligence. John Wiley & Sons.
Ghazzai, H., Yaacoub, E., Alouini, M.-S., Dawy, Z., & Abu-Dayya, A. (2016). Optimized LTE Cell Planning With Varying Spatial and Temporal User Densities. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 1575-1589.
Luna Valero, F. (2008). Meta-heurísticas avanzadas para problemas reales en redes de telecomunicaciones. Málaga: UNIVERSIDAD DE MÁLAGA.
Mouly, M., & Pautet, M. B. (1992). The GSM System for Mobile Communications. France: Paliseau.
Wang, S., Zhao, W., & Wang, C. (2015). Budgeted Cell Planning for Cellular Networks With Small Cells. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 4797-4806.
Wang, Y.-C., & Chuang, C.-A. (2015). Efficient eNB deployment strategy for heterogeneous cells in 4G LTE systems. Computer Networks, 297-312.
Xu, X., Saad, W., Zhang, X., Xu, X., & Zhou, S. (2015). Joint Deployment of Small Cells and Wireless Backhaul Links in Next-Generation Networks. IEEE COMMUNICATIONS LETTERS, 2250-2253.
Zhao, W., Wang, S., Wang, C., & Wu, X. (2014). Cell Planning for Heterogeneous Networks: An Approximation Algorithm. IEEE INFOCOM, 1087-1095.
Zhuma, E., & Puris, A. (2015). Asignación de frecuencias en redes móviles GSM utilizando Meta- Heurística ACO. Publicando, 47-64.

Published

2017-03-31

How to Cite

Viera Carcache, O., Vinces Llaguno, L., Guerrero Goyes, K., & Marcillo Vera, F. (2017). Applying Ant Colony Optimization to the Problem of Cell Planning in Mobile Telephone System Radio Network. Enfoque UTE, 8(2), pp. 56 - 65. https://doi.org/10.29019/enfoqueute.v8n2.156

Issue

Section

Miscellaneous