• DocumentCode
    603293
  • Title

    Mobile Antenna Placement Using Combination of Genetic Algorithm and Learning Automata

  • Author

    Masoudi, Y. ; Lotfi, S. ; Laleh, E. ; Fathy, F.

  • Author_Institution
    Comput. Sci. Dept., Shahid Madani Univ., Tabriz, Iran
  • fYear
    2013
  • fDate
    6-8 April 2013
  • Firstpage
    22
  • Lastpage
    28
  • Abstract
    One of the issue in using of mobile antenna is determining of mobile antenna station in order to proper service. Difference ray of mobile antenna station and their placement and geographical qualification are the factors that caused the problem of mobile antenna antennas be np_hard optimization problem. In this paper in order to finding proper answers for this problem, the combination of genetic algorithm and learning automata are used. Our purpose is that the specified area be covered and the overlapping of mobile antenna station be minimum. In this paper proposed master-slave automata. One of the automata play master automata role and others plays slave automata roles. In last work, actual environment, descent of frequency dosn´t considered. In the end of paper, proposed algorithm compared with other famous algorithms. Results shows that proposed algorithm is better than others from product result and cost effective aspect.
  • Keywords
    genetic algorithms; learning automata; mobile antennas; genetic algorithm; geographical qualification; learning automata; master automata role; master-slave automata; mobile antenna placement; mobile antenna station; np_hard optimization problem; Biological cells; Genetic algorithms; Indexes; Learning automata; Mobile antennas; Mobile communication; frequency; genetic algorithm; learning automata; mobile antenna; placement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Systems and Network Technologies (CSNT), 2013 International Conference on
  • Conference_Location
    Gwalior
  • Print_ISBN
    978-1-4673-5603-9
  • Type

    conf

  • DOI
    10.1109/CSNT.2013.13
  • Filename
    6524349