• DocumentCode
    1423693
  • Title

    QR Decomposition-Based Matrix Inversion for High Performance Embedded MIMO Receivers

  • Author

    Ma, Lei ; Dickson, Kevin ; McAllister, John ; McCanny, John

  • Author_Institution
    Inst. of Electron., Commun. & Inf. Technol. (ECIT), Queen´´s Univ. Belfast, Belfast, UK
  • Volume
    59
  • Issue
    4
  • fYear
    2011
  • fDate
    4/1/2011 12:00:00 AM
  • Firstpage
    1858
  • Lastpage
    1867
  • Abstract
    Real-time matrix inversion is a key enabling technology in multiple-input multiple-output (MIMO) communications systems, such as 802.11n. To date, however, no matrix inversion implementation has been devised which supports real-time operation for these standards. In this paper, we overcome this barrier by presenting a novel matrix inversion algorithm which is ideally suited to high performance floating-point implementation. We show how the resulting architecture offers fundamentally higher performance than currently published matrix inversion approaches and we use it to create the first reported architecture capable of supporting real-time 802.11n operation. Specifically, we present a matrix inversion approach based on modified squared Givens rotations (MSGR). This is a new QR decomposition algorithm which overcomes critical limitations in other QR algorithms that prohibits their application to MIMO systems. In addition, we present a novel modification that further reduces the complexity of MSGR by almost 20%. This enables real-time implementation with negligible reduction in the accuracy of the inversion operation, or the BER of a MIMO receiver based on this.
  • Keywords
    MIMO communication; error statistics; matrix inversion; radio receivers; BER; MIMO receiver; QR decomposition-based matrix inversion; floating-point implementation; modified squared Givens rotation; multiple-input multiple-output communication system; BLAST; QR decomposition; matrix inversion; multiple-input multiple-output (MIMO);
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2011.2105485
  • Filename
    5685579