• DocumentCode
    3485036
  • Title

    Applying genetic algorithms to the data traffic scheduling and performance analysis of a long-term evolution system

  • Author

    Hsien-Wei Tseng ; Yang-Han Lee ; Wei-Chen Lee ; Yih-Guang Jan ; Chorng-Ren Sheu

  • Author_Institution
    Dept. of Comput. & Commun. Eng., De Lin Inst. of Technol., Taipei, Taiwan
  • fYear
    2012
  • fDate
    4-7 Nov. 2012
  • Firstpage
    183
  • Lastpage
    188
  • Abstract
    This study developed a superior transmission resource allocation method using genetic algorithms. The convergence properties of genetic algorithms were employed to increase the transmission resource use efficiency of a base station, allowing users to access wider bandwidths and improving the system throughput and packet service rates of a multicarrier operation. This study also determined the genetic algorithm convergence time and found that the convergence time required for actual calculation was significantly less than one radio frame duration. Finally, the resource allocation results were simulated with and without the genetic algorithm to compare the performance differences.
  • Keywords
    Long Term Evolution; convergence; genetic algorithms; resource allocation; scheduling; telecommunication traffic; bandwidths; convergence property; data traffic scheduling; genetic algorithm convergence time; genetic algorithms; long-term evolution system; multicarrier operation; packet service rates; performance analysis; radio frame duration; superior transmission resource allocation method; system throughput; transmission resource use efficiency; Biological cells; Convergence; Genetic algorithms; Long Term Evolution; Resource management; Throughput; Time frequency analysis; Genetic algorithm; multicarrier operation; resource allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Signal Processing and Communications Systems (ISPACS), 2012 International Symposium on
  • Conference_Location
    New Taipei
  • Print_ISBN
    978-1-4673-5083-9
  • Electronic_ISBN
    978-1-4673-5081-5
  • Type

    conf

  • DOI
    10.1109/ISPACS.2012.6473477
  • Filename
    6473477