• DocumentCode
    1393372
  • Title

    SAGE algorithms for multipath detection and parameter estimation in asynchronous CDMA systems

  • Author

    Logothetis, Andrew ; Carlemalm, Catharina

  • Author_Institution
    Div. of Autom. Control, R. Inst. of Technol., Stockholm, Sweden
  • Volume
    48
  • Issue
    11
  • fYear
    2000
  • fDate
    11/1/2000 12:00:00 AM
  • Firstpage
    3162
  • Lastpage
    3174
  • Abstract
    Algorithms to estimate blindly the parameters and input sequences for a multiuser asynchronous code division multiple access (CDMA) system are proposed. The communication system is modeled as a frequency selective fading channel with multipath propagation, where the number of active propagation channels is unknown and highly time varying. Estimates of input sequences and unknown parameters are jointly computed via the SAGE algorithm. The SAGE algorithm provides a unified approach in combining jointly multiuser detection and parameter estimation in an optimal way. Depending on the realizations of the SAGE algorithm, well-known state and parameter estimation schemes of various complexities are optimally combined
  • Keywords
    AWGN channels; code division multiple access; fading channels; multipath channels; parameter estimation; sequences; signal detection; state estimation; time-varying channels; SAGE algorithms; active propagation channels; asynchronous CDMA systems; communication system; complexities; frequency selective fading channel; input sequences; multipath detection; multipath propagation; multiuser asynchronous code division multiple access system; parameter estimation; state estimation; unknown parameters; AWGN; Detectors; Fading; Frequency; Iterative algorithms; Maximum likelihood detection; Maximum likelihood estimation; Multiaccess communication; Multiuser detection; Parameter estimation;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.875473
  • Filename
    875473