• DocumentCode
    4499
  • Title

    Lossy Joint Source-Channel Coding in the Finite Blocklength Regime

  • Author

    Kostina, Victoria ; Verdu, Sergio

  • Author_Institution
    Dept. of Electr. Eng., Princeton Univ., Princeton, NJ, USA
  • Volume
    59
  • Issue
    5
  • fYear
    2013
  • fDate
    May-13
  • Firstpage
    2545
  • Lastpage
    2575
  • Abstract
    This paper finds new tight finite-blocklength bounds for the best achievable lossy joint source-channel code rate, and demonstrates that joint source-channel code design brings considerable performance advantage over a separate one in the nonasymptotic regime. A joint source-channel code maps a block of k source symbols onto a length-n channel codeword, and the fidelity of reproduction at the receiver end is measured by the probability ε that the distortion exceeds a given threshold d. For memoryless sources and channels, it is demonstrated that the parameters of the best joint source-channel code must satisfy nC - kR(d) ≈ √(nV + k V(d)) Q-1(ε), where C and V are the channel capacity and channel dispersion, respectively; R(d) and V(d) are the source rate-distortion and rate-dispersion functions; and Q is the standard Gaussian complementary cumulative distribution function. Symbol-by-symbol (uncoded) transmission is known to achieve the Shannon limit when the source and channel satisfy a certain probabilistic matching condition. In this paper, we show that even when this condition is not satisfied, symbol-by-symbol transmission is, in some cases, the best known strategy in the nonasymptotic regime.
  • Keywords
    Gaussian channels; block codes; channel capacity; combined source-channel coding; probability; rate distortion theory; Shannon limit; block code; channel capacity; channel dispersion; finite-blocklength bound regime; length-n channel codeword; lossy joint source-channel coding; memoryless source code; nonasymptotic regime; probabilistic matching condition; probability; receiver reproduction; source rate-dispersion function; source rate-distortion function; standard Gaussian complementary cumulative distribution function; symbol-by-symbol uncoded transmission; Channel coding; Dispersion; Distortion measurement; Gaussian approximation; Joints; Source coding; Achievability; Shannon theory; converse; finite blocklength regime; joint source-channel coding (JSCC); lossy source coding; memoryless sources; rate-distortion theory;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2013.2238657
  • Filename
    6408177