• DocumentCode
    2253361
  • Title

    A scalable MIMO detection architecture with non-sorted multiple-candidate selection

  • Author

    Chiu, Po-Lin ; Huang, Yuan-Hao

  • Author_Institution
    Dept. of Commun. Eng., Nat. Chiao-Tung Univ., Hsinchu, Taiwan
  • fYear
    2009
  • fDate
    24-27 May 2009
  • Firstpage
    689
  • Lastpage
    692
  • Abstract
    In this paper, we propose a QR-based MIMO detection algorithm and its architecture based on a non-sorted multiple-candidate selection process. The proposed multiple-candidate selection process can mitigate the error propagation problem in the general QR-SIC detection, and therefore the detection probability is increased. This algorithm requires only 24% of the computational complexity of the V-BLAST, which is only slightly larger than that of the conventional QR-SIC algorithm. Besides, the proposed algorithm features high flexibility between the complexity and the performance, and it can even reach the performance of ML detection for the high performance system. Furthermore, the flexible selection approach requires no sorting operation like traditional K-best algorithm. Thus, a simple scalable VLSI architecture can be constructed for different MIMO configurations.
  • Keywords
    MIMO communication; VLSI; computational complexity; error statistics; matrix decomposition; maximum likelihood detection; K-best algorithm; ML detection; QR-SIC detection algorithm; QR-based MIMO detection algorithm; V-BLAST; computational complexity; detection probability; error propagation mitigation problem; matrix decomposition; nonsorted multiple-candidate selection process; scalable VLSI architecture; sorting operation; Additive white noise; Computational complexity; Detection algorithms; Detectors; MIMO; Matrix decomposition; Receiving antennas; Sorting; Transmitting antennas; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2009. ISCAS 2009. IEEE International Symposium on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4244-3827-3
  • Electronic_ISBN
    978-1-4244-3828-0
  • Type

    conf

  • DOI
    10.1109/ISCAS.2009.5117842
  • Filename
    5117842