• DocumentCode
    2253177
  • Title

    A DRA scheme based on Hopfield neural networks methodology

  • Author

    García, N. ; Pérez-Romero, J.

  • Author_Institution
    Univ. Pompeu Fabra, Barcelona
  • fYear
    2006
  • fDate
    16-19 May 2006
  • Firstpage
    583
  • Lastpage
    586
  • Abstract
    This paper proposes a dynamic resource allocation (DRA) algorithm that makes use of the Hopfield neural network (HNN) methodology, which provides a fast way of finding the optimum resource when formulated as a combinational problem. The proposed algorithm is applied to both the scheduling of downlink transmissions in a CDMA scenario with delay-oriented services, and real time services, although by a proper modification of the constraints imposed in the energy function, it could be easily extended to other services or access technologies. The algorithm is evaluated by means of simulations, revealing its ability to adapt to the specific service and traffic conditions. Finally, the convergence issues related to HNN methodology are considered in the light of the obtained results
  • Keywords
    Hopfield neural nets; code division multiple access; convergence; resource allocation; telecommunication computing; telecommunication services; telecommunication traffic; CDMA scenario; DRA scheme; Hopfield neural networks methodology; combinational problem; convergence issues; delay-oriented services; downlink transmission scheduling; dynamic resource allocation algorithm; energy function; optimum resource; real time services; traffic conditions; Bit rate; Delay effects; Downlink; Electronic mail; Hopfield neural networks; Multiaccess communication; Quality of service; Real time systems; Resource management; Throughput;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrotechnical Conference, 2006. MELECON 2006. IEEE Mediterranean
  • Conference_Location
    Malaga
  • Print_ISBN
    1-4244-0087-2
  • Type

    conf

  • DOI
    10.1109/MELCON.2006.1653168
  • Filename
    1653168