• DocumentCode
    1768987
  • Title

    A low-complexity composite QR decomposition architecture for MIMO detector

  • Author

    Ji-Hwan Yoon ; Dongyeob Shin ; Jongsun Park

  • Author_Institution
    Sch. of Electr. Eng., Korea Univ., Seoul, South Korea
  • fYear
    2014
  • fDate
    1-5 June 2014
  • Firstpage
    1692
  • Lastpage
    1695
  • Abstract
    This paper presents a low complexity QR decomposition (QRD) architecture for MIMO detector. In the proposed approach, various CORDIC-based QRD algorithms are efficiently combined together to reduce the computational complexity of the QRD hardware. Based on the computational complexity analysis on various QRD algorithms, a low complexity approach is selected at each stage of QRD process. The proposed QRD architecture can be applied to any arbitrary dimension of channel matrix, and the complexity reduction grows with the increasing matrix dimension. Our QR decomposition hardware was implemented using Samsung 0.13 μm technology. The numerical results show that the proposed architecture achieves 47% increase in the QAR (QRD Rate/Gate count) with 28.1% power savings over the conventional Householder CORDIC-based architecture for the 4x4 matrix decomposition.
  • Keywords
    MIMO communication; computational complexity; matrix decomposition; signal detection; CORDIC-based QRD algorithms; Householder CORDIC-based architecture; MIMO detector; QRD hardware; QRD rate/gate count; Samsung technology; channel matrix; computational complexity analysis; low complexity QR decomposition architecture; low-complexity composite; matrix decomposition; matrix dimension; size 0.13 mum; Algorithm design and analysis; Computational complexity; Computer architecture; Hardware; MIMO; Matrix decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (ISCAS), 2014 IEEE International Symposium on
  • Conference_Location
    Melbourne VIC
  • Print_ISBN
    978-1-4799-3431-7
  • Type

    conf

  • DOI
    10.1109/ISCAS.2014.6865479
  • Filename
    6865479