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  • Research Article
  • Open Access

The Displacement of Base Station in Mobile Communication with Genetic Approach

EURASIP Journal on Wireless Communications and Networking20082008:580761

  • Received: 5 July 2007
  • Accepted: 2 March 2008
  • Published:


This paper addresses the displacement of a base station with optimization approach. A genetic algorithm is used as optimization approach. A new representation that describes base station placement, transmitted power with real numbers, and new genetic operators is proposed and introduced. In addition, this new representation can describe the number of base stations. For the positioning of the base station, both coverage and economy efficiency factors were considered. Using the weighted objective function, it is possible to specify the location of the base station, the cell coverage, and its economy efficiency. The economy efficiency indicates a reduction in the number of base stations for cost effectiveness. To test the proposed algorithm, the proposed algorithm was applied to homogeneous traffic environment. Following this, the proposed algorithm was applied to an inhomogeneous traffic density environment in order to test it in actual conditions. The simulation results show that the algorithm enables the finding of a near optimal solution of base station placement, and it determines the efficient number of base stations. Moreover, it can offer a proper solution by adjusting the weighted objective function.


  • Genetic Algorithm
  • Transmitted Power
  • Optimization Approach
  • Mobile Communication
  • Economy Efficiency

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Authors’ Affiliations

Wireless system research group, Electronics and Telecommunications Research Institute, (ETRI), 161 Gajeong-Dong, Yuseong-Gu, Daejeon, 305-700, South Korea
The school of Electrical and Computer Engineering, Chungbuk National University, 12 Gaeshin-Dong, Heungduk-Gu, ChungJu, 361-763, South Korea


© Yong Seouk Choi et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.