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Genetic Algorithms with Stochastic Ranking for Optimal Channel Assignment in Mobile Communications

  • Lipo Wang
  • Wen Gu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3314)

Abstract

Optimal channel assignment can enhance traffic capacity of a cellular mobile network and decrease interference between calls, thereby improving service quality and customer satisfaction. We combine genetic algorithms with stochastic ranking, to solve the problem of assigning calls in a cellular mobile network to frequency channels in such a way that interference between calls is minimized, while demands for channels are satisfied. Simulation results showed that this approach is able to further improve on the results obtained by some other techniques.

Keywords

Genetic Algorithm Penalty Function Channel Assignment Vehicular Technology Penalty Coefficient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Lipo Wang
    • 1
    • 2
  • Wen Gu
    • 2
  1. 1.College of Information EngineeringXiangtan UniversityXiangtanChina
  2. 2.School of Electrical and Electronic EngineeringNanyang Technological UniversitySingapore

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