• DocumentCode
    658898
  • Title

    A 0.18nJ/Matrix QR decomposition and lattice reduction processor for 8×8 MIMO preprocessing

  • Author

    Chun-Fu Liao ; Jhong-Yu Wang ; Yuan-Hao Huang

  • Author_Institution
    Dept. of Electr. Eng., Nat. Tsing-Hua Univ., Hsinchu, Taiwan
  • fYear
    2013
  • fDate
    11-13 Nov. 2013
  • Firstpage
    161
  • Lastpage
    164
  • Abstract
    This study presents a joint QR decomposition and lattice reduction processor for 8×8 multiple-input multiple-output (MIMO) systems. The proposed algorithm enhances the BER performance by lattice reduction and reduces the hardware cost by sharing computation units and removing redundant operations. This processor can be reconfigured as three different modes, including joint QR decomposition and lattice reduction, lattice reduction, and QR decomposition. The proposed processor was implemented in TSMC 90nm 1P9M CMOS technology. The maximum throughput is 1.1 M matrix/s for QR decomposition, and 0.5 M matrix/s for the lattice reduction, and 0.33 M matrix/s for the joint QR decomposition and lattice reduction at a power consumption of 31.2 mW. The energy efficiency achieves 0.18nJ/matrix for the 8×8 MIMO preprocessing including both QR decomposition and lattice reduction.
  • Keywords
    CMOS integrated circuits; MIMO communication; error statistics; matrix decomposition; radiofrequency integrated circuits; BER performance; MIMO preprocessing; TSMC 1P9M CMOS technology; energy efficiency; hardware cost reduction; lattice reduction; lattice reduction processor; matrix QR decomposition; multiple-input multiple-output system; power 31.2 mW; size 90 nm; Algorithm design and analysis; Detectors; Hardware; Joints; Lattices; MIMO; Matrix decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Solid-State Circuits Conference (A-SSCC), 2013 IEEE Asian
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4799-0277-4
  • Type

    conf

  • DOI
    10.1109/ASSCC.2013.6691007
  • Filename
    6691007