• DocumentCode
    2609477
  • Title

    A New MIMO Detection Algorithm Based on the Gaussian Graphical Model

  • Author

    Teeti, Mohammed ; Liu, YingZhuang ; Sun, Jun

  • Author_Institution
    Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2012
  • fDate
    6-9 May 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The graphical models have been proven to be a very powerful and potential framework for addressing the inference problems. In this paper, we propose a new graphical model based algorithm for the detection of MIMO systems. The main feature of the algorithm lies in that it is implemented as a MRF-like graph, when combined with the Gaussian approximation and vector-based inference, our algorithm can lead to very promising performance, especially when the constellation size is small, with just linear complexity per symbol and memory requirement increases linearly with the number of transmit antennas. Simulation results collaborate with the analytical results, hence verifying the appeal of the algorithm for practical applications.
  • Keywords
    Gaussian processes; MIMO communication; Markov processes; approximation theory; graph theory; transmitting antennas; Gaussian approximation; Gaussian graphical model; MIMO detection algorithm; MRF-like graph; Markov random field; constellation size; linear complexity; memory requirement; transmit antenna; vector-based inference; Approximation algorithms; Bit error rate; Complexity theory; Damping; Graphical models; MIMO; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Technology Conference (VTC Spring), 2012 IEEE 75th
  • Conference_Location
    Yokohama
  • ISSN
    1550-2252
  • Print_ISBN
    978-1-4673-0989-9
  • Electronic_ISBN
    1550-2252
  • Type

    conf

  • DOI
    10.1109/VETECS.2012.6239967
  • Filename
    6239967