• DocumentCode
    1499401
  • Title

    Reduced-Complexity ML Signal Detection for Spatially Multiplexed Signal Transmission Over MIMO Systems With Two Transmit Antennas

  • Author

    Woo, Hyun-Myung ; Kim, Jaekwon ; Yi, Joo-Hyun ; Cho, Yong-Soo

  • Author_Institution
    Comput. & Telecommun. Eng. Div., Yonsei Univ., Wonju, South Korea
  • Volume
    59
  • Issue
    2
  • fYear
    2010
  • Firstpage
    1036
  • Lastpage
    1041
  • Abstract
    In this paper, we address spatially multiplexed (SM) multiple-input-multiple-output (MIMO) systems that are expected to be used in next-generation mobile communication systems that require high-speed data transmission. The data-transmission rate of an SM MIMO system increases in proportion to the number of spatial streams it transmits. However, it is hard to implement large numbers of spatial streams due to the spatial limits of mobile units and the high cost of installing many antennas. In this paper, we focus on the case of two spatial streams and propose a novel signal-detection technique. We first define the bidirectional detectability of a 2-D complex vector, and using the fact that only a small number of vectors, including the maximum-likelihood (ML) solution vector, satisfy the bidirectional detectability, we reduce the search space, thereby enabling efficient ML signal detection at the receiver.
  • Keywords
    MIMO communication; channel estimation; maximum likelihood estimation; multiplexing; signal detection; 2D complex vector; MIMO systems; bidirectional detectability; high speed data transmission; maximum likelihood solution vector; next generation mobile communication; reduced complexity maximum likelihood signal detection; spatial streams; spatially multiplexed multiple input multiple output systems; spatially multiplexed signal transmission; transmit antennas; Maximum-likelihood (ML) signal detection; multiple input–multiple output (MIMO);
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/TVT.2009.2034459
  • Filename
    5286271