• DocumentCode
    2558917
  • Title

    Effective SNR mapping algorithms for link prediction model in 802.16e

  • Author

    Aguilar, Fernando López ; Cidre, Gorka Rubio ; París, Javier Regidor

  • Author_Institution
    Telefonica R&D, Madrid, Spain
  • fYear
    2009
  • fDate
    12-14 Oct. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Link layer abstraction is crucial both the cross layer simulation and design and the interface to complete a system level simulator. The calibration takes an important role within this design. In this paper we have used several kinds of algorithms like EESM, CESM and LESM for the instantaneous channel, calibration and evaluation of the link level interface in WiMAX system 802.16e. In order to have real world situations, we are also using the adaptative modulation and coding (AMC), hybrid automatic repeat request (H-ARQ) and PUSC/FUSC permutation besides of OFDM systems. Plenty of simulations were made for evaluate the different algorithms and the results show that EESM has better accuracy that the others.
  • Keywords
    OFDM modulation; WiMax; adaptive modulation; automatic repeat request; calibration; encoding; telecommunication standards; CESM; EESM; LESM; OFDM systems; PUSC/FUSC permutation; SNR mapping algorithms; WiMAX system 802.16e; adaptative modulation; calibration; coding; cross layer simulation; fully used sub-carrier; hybrid automatic repeat request; link layer abstraction; link prediction; partially used sub-carrier; Automatic repeat request; Calibration; Diversity reception; Modulation coding; OFDM modulation; Prediction algorithms; Predictive models; Scalability; Tiles; WiMAX; 802.16e; CESM; EESM; H-ARQ; LESM; Link layer abstraction; PUSC/FUSC; SIMO; SIR Mapping; System level simulator; WiMAX Mobile;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ultra Modern Telecommunications & Workshops, 2009. ICUMT '09. International Conference on
  • Conference_Location
    St. Petersburg
  • Print_ISBN
    978-1-4244-3942-3
  • Electronic_ISBN
    978-1-4244-3941-6
  • Type

    conf

  • DOI
    10.1109/ICUMT.2009.5345444
  • Filename
    5345444