• DocumentCode
    2076535
  • Title

    Performance analysis of RLS and VSS-LMS channel estimation techniques for 4G MIMO OFDM systems

  • Author

    Hossain, M. ; Farhad, S.M. ; Riasat, Md Tauseef

  • Author_Institution
    Electron. & Commun. Eng., Khulna Univ. of Eng. & Technol., Khulna, Bangladesh
  • fYear
    2012
  • fDate
    22-24 Dec. 2012
  • Firstpage
    267
  • Lastpage
    270
  • Abstract
    In this paper recursive least (RLS) square and variable step size least mean (VSS-LMS) square adaptive channel estimator are described for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Both the techniques uses adaptive estimator which are capable of updating the parameters of estimator continuously and therefore knowledge of channel and noise statistics are not necessary, only knowledge of receive signal is required. From the simulation result it is observed that RLS CE method works better in terms of quick convergence rate than VSS-LMS CE for MIMO OFDM system. In addition, the utilization of more multiple antennas at the transmitter and/or receiver provides a much higher performance compared with fewer antennas.
  • Keywords
    4G mobile communication; MIMO communication; OFDM modulation; adaptive estimation; antenna arrays; channel estimation; least mean squares methods; 4G MIMO OFDM systems; RLS CE method; RLS techniques; VSS-LMS CE; VSS-LMS channel estimation techniques; adaptive estimator; multiple antennas; multiple input multiple output system; noise statistics; orthogonal frequency division multiplexing system; receive signal; receiver; recursive least square technique; transmitter; variable step size least mean square adaptive channel estimator; MIMO; OFDM; RLS; VSS-LMS;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology (ICCIT), 2012 15th International Conference on
  • Conference_Location
    Chittagong
  • Print_ISBN
    978-1-4673-4833-1
  • Type

    conf

  • DOI
    10.1109/ICCITechn.2012.6509724
  • Filename
    6509724