• DocumentCode
    56433
  • Title

    An Improved Subspace-Based Algorithm for Blind Channel Identification Using Few Received Blocks

  • Author

    Yen-Chang Pan ; See-May Phoong

  • Author_Institution
    Dept. of EE, Nat. Taiwan Univ., Taipei, Taiwan
  • Volume
    61
  • Issue
    9
  • fYear
    2013
  • fDate
    Sep-13
  • Firstpage
    3710
  • Lastpage
    3720
  • Abstract
    In the last decade, several subspace-based algorithms for blind channel identification in zero-padded systems were introduced. These subspace-based methods are attractive because highly accurate estimates of the channel can be obtained by using only a few received blocks. However, they do not work when applied to the zero-padded orthogonal frequency division multiplexing systems (ZP-OFDM) with virtual carriers. In this paper, we propose two improvements on an earlier subspace-based blind channel estimation method for such systems. Firstly, we introduce a simple noise weighting approach. Unlike most of the earlier methods, the proposed weighting matrix is diagonal and it is independent of the channel noise variance and SNR. By doing so, the performance of previous work is significantly enhanced. Secondly, we extend the blind estimation method to ZP-OFDM systems with virtual carriers. Simulations are carried out to demonstrate the merits of the proposed method.
  • Keywords
    OFDM modulation; channel estimation; matrix algebra; SNR; ZP-OFDM system; blind channel estimation method; blind channel identification; channel noise variance; subspace-based algorithm; weighting matrix; zero-padded orthogonal frequency division multiplexing system; Channel estimation; Estimation; Indexes; OFDM; Signal to noise ratio; Vectors; Channel identification; blind method; zero-padded orthogonal frequency division multiplexing (ZP-OFDM);
  • fLanguage
    English
  • Journal_Title
    Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0090-6778
  • Type

    jour

  • DOI
    10.1109/TCOMM.2013.072213.120895
  • Filename
    6567867