• DocumentCode
    791747
  • Title

    A fast block-based nonlinear decoding algorithm for ΣΔ modulators

  • Author

    Hein, Soren

  • Author_Institution
    Semicond. Div., Siemens AG, Munich, Germany
  • Volume
    43
  • Issue
    6
  • fYear
    1995
  • fDate
    6/1/1995 12:00:00 AM
  • Firstpage
    1360
  • Lastpage
    1367
  • Abstract
    Previous work has established that the digital output of a ΣΔ modulator as an A/D converter contains more information about the analog input than is extracted with conventional linear filtering. Under reasonable mathematical assumptions, optimal nonlinear decoding of the digital output can achieve significantly larger signal-to-noise ratios than linear filtering. However, the hitherto proposed decoding algorithms only demonstrate conceptual feasibility and are impractical from a computational point of view. We present a new block-based decoding algorithm that, like previous work, employs projections onto convex sets. The algorithm owes its speed to a change of projection norm, an accelerated convergence scheme, and a decimation-like subsampling; it is on the order of 104-105 times faster than one previously published algorithm for typical parameter values, and about 2-10 times slower than linear decoding. The new algorithm is applicable to all currently popular ΣΔ architectures.
  • Keywords
    computational complexity; convergence of numerical methods; decoding; modulators; sigma-delta modulation; signal sampling; ΣΔ architectures; ΣΔ modulators; A/D converter; ADC; accelerated convergence scheme; analog input; block-based nonlinear decoding algorithm; decimation-like subsampling; digital output; fast algorithm; optimal nonlinear decoding; parameter values; projections onto convex sets; sigma-delta modulation; sigma-delta modulators; signal-to-noise ratios; Acceleration; Bandwidth; Convergence; Data mining; Delta modulation; Digital modulation; Iterative decoding; Maximum likelihood detection; Signal to noise ratio; Timing;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.388850
  • Filename
    388850