• DocumentCode
    1465849
  • Title

    Iterative Superlinear-Convergence SVD Beamforming Algorithm and VLSI Architecture for MIMO-OFDM Systems

  • Author

    Zhan, Cheng-Zhou ; Chen, Yen-Liang ; Wu, An-Yeu

  • Author_Institution
    Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
  • Volume
    60
  • Issue
    6
  • fYear
    2012
  • fDate
    6/1/2012 12:00:00 AM
  • Firstpage
    3264
  • Lastpage
    3277
  • Abstract
    In this paper, we propose a singular value decomposition (SVD) algorithm with superlinear-convergence rate, which is suitable for the beamforming mechanism in MIMO-OFDM channels with short coherent time, or short training sequence. The proposed superlinear-convergence SVD (SL-SVD) algorithm has the following features: 1) superlinear-convergence rate; 2) the ability of being extended smaller numbers of transmit and receive antennas; 3) being insensitive to dynamic range problems during the iterative process in hardware implementations; and 4) low computational cost. We verify the proposed design by using the VLSI implementation with CMOS 90 nm technology. The post-layout result of the design has the feature of 0.48 core area and 18 mW power consumption. Our design can achieve 7 M channel-matrices/s, and can be extended to deal with different transmit and receive antenna sets.
  • Keywords
    CMOS integrated circuits; MIMO communication; OFDM modulation; VLSI; antenna arrays; array signal processing; convergence of numerical methods; iterative methods; receiving antennas; singular value decomposition; transmitting antennas; CMOS technology; MIMO-OFDM systems; VLSI Architecture; channel-matrices; hardware implementations; iterative superlinear-convergence SVD beamforming algorithm; low computational cost; multiple-input multiple-output channels; orthogonal frequency division multiplexing; post-layout; receive antenna sets; short coherent time; short training sequence; singular value decomposition; superlinear-convergence rate; transmit antenna sets; Array signal processing; Computational efficiency; MIMO; Matrix decomposition; Receiving antennas; Very large scale integration; Beamforming; multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM); precoding; singular value decomposition (SVD); superlinear;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2012.2190405
  • Filename
    6166356