• DocumentCode
    2732081
  • Title

    Reduced complexity Sphere Decoding

  • Author

    Li, Boyu ; Ayanoglu, Ender

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Univ. of California - Irvine, Irvine, CA, USA
  • fYear
    2011
  • fDate
    4-8 July 2011
  • Firstpage
    147
  • Lastpage
    151
  • Abstract
    In Multiple-Input Multiple-Output (MIMO) systems, Sphere Decoding (SD) can achieve performance equivalent to full search Maximum Likelihood (ML) decoding with reduced complexity. Several researchers reported techniques that reduce the complexity of SD further. In this paper, a new technique is introduced which decreases the computational complexity of SD substantially, without sacrificing performance. The reduction is accomplished by deconstructing the decoding metric to decrease the number of computations and exploiting the structure of a lattice representation. Simulation results show that this approach achieves substantial gains for the average number of real multiplications and real additions needed to decode one transmitted vector symbol. As an example, for a 4 × 4 MIMO system, the gains in the number of multiplications are 85% with 4-QAM and 90% with 64-QAM, at low SNR.
  • Keywords
    MIMO communication; communication complexity; maximum likelihood decoding; quadrature amplitude modulation; MIMO system; QAM; SNR; computational complexity; decoding metric; lattice representation; maximum likelihood decoding; multiple-input multiple-output system; sphere decoding; transmitted vector symbol; Complexity theory; Lattices; MIMO; Maximum likelihood decoding; Modulation; Signal to noise ratio; Low Computational Complexity; MIMO; ML Decoding; SD;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications and Mobile Computing Conference (IWCMC), 2011 7th International
  • Conference_Location
    Istanbul
  • Print_ISBN
    978-1-4244-9539-9
  • Type

    conf

  • DOI
    10.1109/IWCMC.2011.5982522
  • Filename
    5982522