• DocumentCode
    764598
  • Title

    A finite precision analysis of the block-gradient adaptive data-driven echo canceller

  • Author

    Cioffi, John M. ; Ho, Mantak

  • Author_Institution
    Dept. of Electr. Eng., Stanford Univ., CA, USA
  • Volume
    40
  • Issue
    5
  • fYear
    1992
  • fDate
    5/1/1992 12:00:00 AM
  • Firstpage
    940
  • Lastpage
    946
  • Abstract
    The block-gradient (block LMS) algorithm´s finite precision performance in the data-driven echo canceller application is analyzed. From both the analysis and simulation results, it was found that the block LMS requires significantly less precision than the standard LMS algorithm. The analysis also shows how higher convergence and tracking speeds may be traded for an improvement in precision requirements. The authors derive formulae that can be used to accurately compute echo rejection levels as a function of precision, signal powers, step-size, block length, and echo canceller length. The utility of the formulae is demonstrated by showing performance levels for a typical V.32bis full-duplex voiceband modem operating at a transmission rate of 14.4 kbit/s (7200 Hz sampling rate), and for a high-speed digital subscriber line echo canceller operating at a sampling rate of 400 kHz
  • Keywords
    data communication equipment; echo suppression; least squares approximations; modems; subscriber loops; 14.4 kbit/s; V.32bis full-duplex voiceband modem; adaptive data-driven echo canceller; block LMS algorithm; block length; block-gradient algorithm; echo canceller length; echo rejection levels; finite precision analysis; high-speed digital subscriber line; higher convergence; sampling rate; signal powers; step-size; telecommunication equipment; tracking speeds; Algorithm design and analysis; Analytical models; Computational modeling; Convergence; DSL; Echo cancellers; Least squares approximation; Modems; Performance analysis; Sampling methods;
  • fLanguage
    English
  • Journal_Title
    Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0090-6778
  • Type

    jour

  • DOI
    10.1109/26.141459
  • Filename
    141459