• DocumentCode
    178954
  • Title

    A 3.8Gb/s large-scale MIMO detector for 3GPP LTE-Advanced

  • Author

    Bei Yin ; Wu, Min ; Guohui Wang ; Dick, Chris ; Cavallaro, J.R. ; Studer, Christoph

  • Author_Institution
    Rice Univ., Houston, TX, USA
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    3879
  • Lastpage
    3883
  • Abstract
    This paper proposes - to the best of our knowledge - the first ASIC design for high-throughput data detection in single carrier frequency division multiple access (SC-FDMA)-based large-scale MIMO systems, such as systems building on future 3GPP LTE-Advanced standards. In order to substantially reduce the complexity of linear soft-output data detection in systems having hundreds of antennas at the base station (BS), the proposed detector builds upon a truncated Neumann series expansion to compute the necessary matrix inverse at low complexity. To achieve high throughput in the 3GPP LTE-A uplink, we develop a systolic VLSI architecture including all necessary processing blocks. We present a corresponding ASIC design that achieves 3.8 Gb/s for a 128 antenna, 8 user 3GPP LTE-A based large-scale MIMO system, while occupying 11.1 mm2 in a TSMC 45nm CMOS technology.
  • Keywords
    3G mobile communication; Long Term Evolution; MIMO communication; application specific integrated circuits; matrix algebra; 3GPP LTE advanced; ASIC design; BS; MIMO detector; MIMO systems; SC-FDMA; base station; bit rate 3.8 Gbit/s; data detection; linear soft-output data detection; matrix inverse; single carrier frequency division multiple access; systolic VLSI architecture; truncated Neumann series expansion; Antennas; Application specific integrated circuits; Approximation methods; Detectors; MIMO; Throughput; Uplink; ASIC design; Large-scale (or massive) MIMO; Neumann series; linear soft-output detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6854328
  • Filename
    6854328