• DocumentCode
    2233166
  • Title

    Divide-and-Conquer Matrix Inversion for Linear MMSE Detection in SDR MIMO Receivers

  • Author

    Eberli, Stefan ; Cescato, Davide ; Fichtner, Wolfgang

  • Author_Institution
    Integrated Syst. Lab., ETH Zurich, Zurich, Switzerland
  • fYear
    2008
  • fDate
    16-17 Nov. 2008
  • Firstpage
    162
  • Lastpage
    167
  • Abstract
    Software-defined radio (SDR) platforms represent a promising approach to facing the demands of the fast evolving field of wireless communications. The flexibility of SDR solutions is typically obtained at the cost of limited processing power, which imposes the use of low-complexity algorithms. This task is particularly challenging within multiple-input multiple-output (MIMO) communication, which is inherently characterized by heavy signal processing load. In this paper, we present a recursive matrix inversion algorithm for Hermitian positive-definite (HPD) matrices. The algorithm exhibits low computational complexity and is thus particularly suited for the HPD matrix inversion required in MIMO minimum mean squared error receivers. The implementation on a design-time configurable VLIW processor, configured with appropriate processing units and fabricated in 0.18 ¿m 1P/6M CMOS technology, demonstrates that real-time operation in IEEE 802.11n-like MIMO-OFDM systems with up to 52 carriers and 3 antennas at the transmitter and at the receiver is possible.
  • Keywords
    Hermitian matrices; MIMO communication; computational complexity; divide and conquer methods; least mean squares methods; matrix inversion; radio receivers; signal detection; software radio; Hermitian positive-definite matrix; SDR MIMO receiver; computational complexity; divide-and-conquer recursive matrix inversion; linear MMSE detection; minimum mean squared error; multiple-input multiple-output communication; signal processing; software-defined radio; wireless communication; CMOS process; CMOS technology; Computational complexity; Costs; MIMO; Process design; Receivers; Signal processing algorithms; VLIW; Wireless communication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    NORCHIP, 2008.
  • Conference_Location
    Tallinn
  • Print_ISBN
    978-1-4244-2492-4
  • Electronic_ISBN
    978-1-4244-2493-1
  • Type

    conf

  • DOI
    10.1109/NORCHP.2008.4738303
  • Filename
    4738303