• DocumentCode
    2066994
  • Title

    A Simplified LMMSE Channel Estimation Algorithm for OFDM Systems

  • Author

    Hu Feng ; Li Jianping

  • Author_Institution
    Sch. of Inf. Eng., Commun. Univ. of China, Beijing, China
  • fYear
    2009
  • fDate
    20-22 Sept. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Orthogonal frequency division multiplexing (OFDM) is a key technique of multi-carrier transmission to meet high data rate requirement of wireless communication. Channel state information (CSI) derived from channel estimation is necessary for receivers to accurately recover the transmitted signals. It is well known that the LMMSE (linear minimum mean square error) algorithm is one of the best linear receivers for OFDM channel estimation, which provides better mean squared error (MSE) performance but requires more computations than others. In this paper, a simplified LMMSE channel estimation algorithm using Fourier Transform technique and an appropriate training-sequences-aided is proposed without loss of MSE performance. Simulation results show that the proposed LMMSE algorithm can effectively lower computational complexity. When adopting 256 pilot symbols in OFDM systems with Rayleigh fading channels, the time spending in channel estimation reduces about a quarter.
  • Keywords
    Fourier transforms; OFDM modulation; Rayleigh channels; channel estimation; least mean squares methods; Fourier transform technique; LMMSE channel estimation algorithm; OFDM system; Rayleigh fading channel; appropriate training-sequences; computational complexity; linear minimum mean square error; linear receiver; multicarrier transmission; orthogonal frequency division multiplexing; wireless communication; Channel estimation; Channel state information; Computational complexity; Computational modeling; Fading; Fourier transforms; Mean square error methods; OFDM; Performance loss; Wireless communication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management and Service Science, 2009. MASS '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4638-4
  • Electronic_ISBN
    978-1-4244-4639-1
  • Type

    conf

  • DOI
    10.1109/ICMSS.2009.5300821
  • Filename
    5300821