• DocumentCode
    2490784
  • Title

    OFDM channel prediction using set-membership affine projection algorithm in time-varying wireless channel

  • Author

    Leite, João P. ; De Carvalho, Paulo H P ; Vieira, Robson D.

  • Author_Institution
    Univ. of Brasilia (UnB), Brasilia, Brazil
  • fYear
    2009
  • fDate
    21-24 June 2009
  • Firstpage
    26
  • Lastpage
    30
  • Abstract
    In order to take advantage of adaptive transmission techniques or multiple antennas, it is necessary to have actual channel state information (CSI) at transmitter and/or receiver. Due to system constraints and the time varying nature of the mobile radio channel, the CSI might be outdated, leading to performance degradation of the system. Channel prediction can provide up-to-date channel state information and reduce capacity loss. This paper presents a channel predictor based on the set-membership affine projection filtering involving an OFDM system. Realistic physical channel model used for standardization is considered to evaluate the performance of the predictor and compare it to well-known adaptive algorithms NLMS and RLS. Simulation results also show the bit-error rate performance and the robustness of the proposed predictor under the specifications of 3GPP Long Term Evolution (LTE).
  • Keywords
    OFDM modulation; affine transforms; channel estimation; mobile radio; time-varying channels; wireless channels; OFDM channel prediction; channel state information; mobile radio channel; set-membership affine projection algorithm; time-varying wireless channel; Adaptive arrays; Channel state information; OFDM; Predictive models; Projection algorithms; Radio transmitters; Receivers; Receiving antennas; Time varying systems; Transmitting antennas; Adaptive Predictors; LTE; channel prediction; orthogonal frequency-division multiplexing (OFDM); time-varying channels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Advances in Wireless Communications, 2009. SPAWC '09. IEEE 10th Workshop on
  • Conference_Location
    Perugia
  • Print_ISBN
    978-1-4244-3695-8
  • Electronic_ISBN
    978-1-4244-3696-5
  • Type

    conf

  • DOI
    10.1109/SPAWC.2009.5161740
  • Filename
    5161740