• DocumentCode
    2045769
  • Title

    Memory-constrained ML-optimal tree search detection

  • Author

    Dai, Yongmei ; Yan, Zhiyuan

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Lehigh Univ., Lehigh, PA
  • fYear
    2008
  • fDate
    19-21 March 2008
  • Firstpage
    1037
  • Lastpage
    1041
  • Abstract
    In this paper, we propose a memory-constrained tree search (MCTS) algorithm for the detection in multiple-input multiple-output (MIMO) systems. The MCTS algorithm offers a wide range of trade-offs between computational complexity and memory requirement, and is guaranteed to achieve the exact maximum-likelihood performance. By tuning the memory size, the MCTS algorithm ranges from being memory-efficient to being computation-efficient with abundant choices in between.We show that the MCTS algorithm visits slightly fewer nodes and requires slightly less memory than the sphere decoding (SD) algorithm in the memory-efficient case, and visits similar number of nodes and requires significantly less memory than the stack algorithm in the computation-efficient case.
  • Keywords
    MIMO systems; computational complexity; tree searching; computational complexity; maximum-likelihood performance; memory requirement; memory-constrained tree search algorithm; multiple-input multiple-output system; sphere decoding algorithm; stack algorithm; tree search detection; Computational complexity; Detection algorithms; Diversity methods; Electronic mail; Hardware; MIMO; Maximum likelihood decoding; Maximum likelihood detection; Receiving antennas; Wireless communication; MIMO; ML; Sphere Decoding; ZF-IC; stack;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Sciences and Systems, 2008. CISS 2008. 42nd Annual Conference on
  • Conference_Location
    Princeton, NJ
  • Print_ISBN
    978-1-4244-2246-3
  • Electronic_ISBN
    978-1-4244-2247-0
  • Type

    conf

  • DOI
    10.1109/CISS.2008.4558671
  • Filename
    4558671