• DocumentCode
    266572
  • Title

    Achievable rates of uplink multiuser massive MIMO systems with estimated channels

  • Author

    Songtao Lu ; Zhengdao Wang

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA, USA
  • fYear
    2014
  • fDate
    8-12 Dec. 2014
  • Firstpage
    3772
  • Lastpage
    3777
  • Abstract
    We study the performance of uplink transmission in a large-scale (massive) MIMO system, where all the transmitters have single antennas and the receiver (base station) has a large number of antennas. Specifically, we first derive the rates that are possible through minimum mean-squared error (MMSE) channel estimation and three possible linear receivers: maximum ratio combining, zero-forcing, and MMSE. Based on the derived rates, we quantify the amount of energy savings that are possible through increased number of base-station antennas or increased coherence interval. We also analyze achievable degrees of freedom of such a system without assuming channel state information at the receiver, which turns out to be the same as that of a point-to-point MIMO channel. Linear receiver is sufficient when the number of users is less than the number of antennas. Otherwise, nonlinear processing is necessary to achieve the full degrees of freedom.
  • Keywords
    MIMO communication; channel estimation; diversity reception; least mean squares methods; MMSE channel estimation; achievable degree-of-freedom; base-station antennas; channel state information; energy savings; full degrees-of-freedom; increased coherence interval; large-scale MIMO system; linear receiver; linear receivers; maximum ratio combining; minimum mean-squared error channel estimation; nonlinear processing; point-to-point MIMO channel; transmitters; uplink multiuser massive MIMO systems; uplink transmission; zero-forcing; Base stations; Channel estimation; MIMO; Receiving antennas; Signal to noise ratio; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Communications Conference (GLOBECOM), 2014 IEEE
  • Conference_Location
    Austin, TX
  • Type

    conf

  • DOI
    10.1109/GLOCOM.2014.7037395
  • Filename
    7037395