• DocumentCode
    1062487
  • Title

    Partial regularisation approach for detection problems in underdetermined linear systems

  • Author

    Chang, X.-W. ; Yang, Xu ; Le-Ngoc, Tho ; Wang, Peng

  • Author_Institution
    Sch. of Comput. Sci., McGill Univ., Montreal, QC
  • Volume
    3
  • Issue
    1
  • fYear
    2009
  • fDate
    1/1/2009 12:00:00 AM
  • Firstpage
    17
  • Lastpage
    24
  • Abstract
    The maximum likelihood detection problem in many underdetermined linear communications systems can be described as an underdetermined integer least squares (ILS) problem. To solve it efficiently, a partial regularisation approach is proposed. The original underdetermined ILS problem is first transformed to an equivalent overdetermined ILS problem by using part of the transmit vector to do the regularisation. Then the overdetermined ILS problem is solved by conventional sphere decoding algorithms. Simulation results indicate that this approach can be much more efficient than other approaches for any square constellation higher than 4QAM.
  • Keywords
    least squares approximations; linear systems; maximum likelihood detection; vectors; QAM; conventional sphere decoding algorithms; maximum likelihood detection problem; partial regularisation approach; signal detection problem; transmit vector; underdetermined integer least squares; underdetermined linear systems;
  • fLanguage
    English
  • Journal_Title
    Communications, IET
  • Publisher
    iet
  • ISSN
    1751-8628
  • Type

    jour

  • DOI
    10.1049/iet-com:20080210
  • Filename
    4745852