• DocumentCode
    2063973
  • Title

    MIMO-OFDM channel estimation based on distributed compressed sensing and Kalman filter

  • Author

    Yun, Tan ; Wenbo, Xu ; Zhiqiang, He ; Baoyu, Tian ; Donghao, Wang

  • Author_Institution
    Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2011
  • fDate
    14-16 Sept. 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    MIMO-OFDM technology combines the advantage of MIMO and OFDM and is widely used in high data rate systems. Traditional channel estimation of MIMO-OFDM suffers from a high cost of large number of pilots. In this paper, we presents a method that combines Kalman filter and distributed compressed sensing (DCS), which can achieve much better performance than least square and pure DCS algorithm with less pilots.
  • Keywords
    Kalman filters; MIMO communication; OFDM modulation; channel estimation; Kalman filter; MIMO-OFDM channel estimation; distributed compressed sensing; high data rate systems; Channel estimation; Compressed sensing; Correlation; Joints; Kalman filters; MIMO; OFDM; Kalman filter; MIMO-OFDM; channel estimation; distributed compressed sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, Communications and Computing (ICSPCC), 2011 IEEE International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4577-0893-0
  • Type

    conf

  • DOI
    10.1109/ICSPCC.2011.6061583
  • Filename
    6061583
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2063973