• DocumentCode
    1136210
  • Title

    Approximating the Gaussian Multiple Description Rate Region Under Symmetric Distortion Constraints

  • Author

    Tian, Chao ; Mohajer, Soheil ; Diggavi, Suhas N.

  • Author_Institution
    Sch. of Comput. & Commun. Sci., Ecole Polytech. Fed. de Lausanne, Lausanne, Switzerland
  • Volume
    55
  • Issue
    8
  • fYear
    2009
  • Firstpage
    3869
  • Lastpage
    3891
  • Abstract
    We consider multiple description (MD) coding for the Gaussian source with K descriptions under the symmetric mean-squared error (MSE) distortion constraints, and provide an approximate characterization of the rate region. We show that the rate region can be sandwiched between two polytopes, between which the gap can be upper-bounded by constants dependent on the number of descriptions, but independent of the distortion constraints. Underlying this result is an exact characterization of the lossless multilevel diversity source coding problem: a lossless counterpart of the MD problem. This connection provides a polytopic template for the inner and outer bounds to the rate region. In order to establish the outer bound, we generalize Ozarow´s technique to introduce a strategic expansion of the original probability space by more than one random variable. For the symmetric rate case with any number of descriptions, we show that the gap between the upper bound and the lower bound for the individual description rate-distortion function is no larger than 0.92 bit. The results developed in this work also suggest that the ldquoseparationrdquo approach of combining successive refinement quantization and lossless multilevel diversity coding is a competitive one, since its performance is only a constant away from the optimum. The results are further extended to general sources under the MSE distortion measure, where a similar but looser bound on the gap holds.
  • Keywords
    mean square error methods; source coding; Gaussian source; MSE distortion; Ozarow technique; distortion constraints; mean-squared error; multilevel diversity source coding; multiple description coding; Chaos; Distortion measurement; Diversity reception; Information theory; Performance loss; Quantization; Random variables; Rate-distortion; Source coding; Upper bound; Multiple descriptions; rate distortion; symmetry;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2009.2023704
  • Filename
    5165169