• DocumentCode
    27724
  • Title

    Pilot Beam Pattern Design for Channel Estimation in Massive MIMO Systems

  • Author

    Song Noh ; Zoltowski, M.D. ; Youngchul Sung ; Love, David J.

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
  • Volume
    8
  • Issue
    5
  • fYear
    2014
  • fDate
    Oct. 2014
  • Firstpage
    787
  • Lastpage
    801
  • Abstract
    In this paper, the problem of pilot beam pattern design for channel estimation in massive multiple-input multiple-output systems with a large number of transmit antennas at the base station is considered, and a new algorithm for pilot beam pattern design for optimal channel estimation is proposed under the assumption that the channel is a stationary Gauss-Markov random process. The proposed algorithm designs the pilot beam pattern sequentially by exploiting the properties of Kalman filtering and the associated prediction error covariance matrices and also the channel statistics such as spatial and temporal channel correlation. The resulting design generates a sequentially-optimal sequence of pilot beam patterns with low complexity for a given set of system parameters. Numerical results show the effectiveness of the proposed algorithm.
  • Keywords
    Gaussian processes; MIMO communication; Markov processes; antenna radiation patterns; channel estimation; covariance matrices; random processes; transmitting antennas; Kalman filtering; base station; channel statistics; massive MIMO system; multiple input multiple output system; optimal channel estimation; pilot beam pattern design; prediction error covariance matrices; stationary Gauss-Markov random process; system parameters; transmit antenna; Channel estimation; Correlation; Covariance matrices; Kalman filters; MIMO; Training; Vectors; Channel estimation; massive MIMO systems; spatio-temporal correlation; training signal design;
  • fLanguage
    English
  • Journal_Title
    Selected Topics in Signal Processing, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    1932-4553
  • Type

    jour

  • DOI
    10.1109/JSTSP.2014.2327572
  • Filename
    6823657