• DocumentCode
    2926045
  • Title

    Genetic algorithm approach for solving radio resource allocation for overlapping MBSFN area

  • Author

    Azman, M.F. ; Tuban, N.F. ; Noordin, K.A. ; Ismail, M.F.

  • Author_Institution
    Electr. Dept., Univ. of Malaya, Kuala Lumpur, Malaysia
  • fYear
    2011
  • fDate
    14-16 Nov. 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Multicast Broadcast Single Frequency Network (MBSFN) is a new technique utilized in 3GPP LTE to deliver Multicast Broadcast Multimedia Service (MBMS) to users. In this paper, we proposed a novel method to allocate different radio resources in overlapping MBSFN area by using Genetic Algorithm (GA). The algorithm would be used to optimize the allocation of radio resource unit in the overlapped areas by finding the best solution to allocate different resources to base stations (eNBs) for delivering different services to different areas. The GA is able to limit the number of RRU to three for up to eight overlapping MBSFN areas. Simulation results show that the proposed method could contribute by providing a set of solution to every dynamically changed topology of MBSFN area.
  • Keywords
    3G mobile communication; Long Term Evolution; genetic algorithms; multicast communication; multimedia communication; radio broadcasting; telecommunication network topology; 3GPP LTE; MBSFN area overlapping; base stations; dynamically changed topology; genetic algorithm approach; multicast broadcast multimedia service; multicast broadcast single frequency network; radio resource allocation; radio resource unit; Biological cells; Digital multimedia broadcasting; Genetic algorithms; Long Term Evolution; Multimedia communication; Resource management; Topology; Genetic Algorithm; Multicast and Broadcast Service Single Frequency Network(MBSFN); OFDMA; Radio Resource Allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Multimedia (ICIM), 2011 International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4577-0988-3
  • Type

    conf

  • DOI
    10.1109/ICIMU.2011.6122734
  • Filename
    6122734