• DocumentCode
    3170733
  • Title

    Immune genetic algorithm-based parameters optimization of cognitive radios

  • Author

    De-Quan Zhou

  • Author_Institution
    Sch. of Inf. Sci. & Tech., Zhe Jiang Forestry Univ., Hangzhou, China
  • fYear
    2009
  • fDate
    3-6 Nov. 2009
  • Firstpage
    468
  • Lastpage
    470
  • Abstract
    Genetic algorithms are best suited for optimization problems. But premature convergence exists when genetic algorithm applied for optimization problems. The immune genetic algorithm (IGA) combined artificial immune system and GA together is presented to overcome this problem. Finally, the IGA is used to solve parameter optimization problems of cognitive radios. Simulation results demonstrate that IGA can rapidly reach an optimal decision.
  • Keywords
    artificial immune systems; cognitive radio; convergence; genetic algorithms; artificial immune system; cognitive radio; immune genetic algorithm; parameter optimization problem; premature convergence; Artificial immune system; Cognitive radios; Genetic algorithms; Multi-objective optimization;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Microwave Technology and Computational Electromagnetics, 2009. ICMTCE. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-84919-140-1
  • Type

    conf

  • DOI
    10.1049/cp.2009.1369
  • Filename
    5521220
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3170733