• DocumentCode
    1254116
  • Title

    Binary lattice vector quantization with linear block codes and affine index assignments

  • Author

    Mehes, Andras ; Zeger, Kenneth

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA
  • Volume
    44
  • Issue
    1
  • fYear
    1998
  • fDate
    1/1/1998 12:00:00 AM
  • Firstpage
    79
  • Lastpage
    94
  • Abstract
    We determine analytic expressions for the performance of some low-complexity combined source-channel coding systems. The main tool used is the Hadamard transform. In particular, we obtain formulas for the average distortion of binary lattice vector quantization with affine index assignments, linear block channel coding, and a binary-symmetric channel. The distortion formulas are specialized to nonredundant channel codes for a binary-symmetric channel, and then extended to affine index assignments on a binary-asymmetric channel. Various structured index assignments are compared. Our analytic formulas provide a computationally efficient method for determining the performance of various coding schemes. One interesting result shown is that for a uniform source and uniform quantizer, the natural binary code is never optimal for a nonsymmetric channel, even though it is known to be optimal for a symmetric channel
  • Keywords
    Hadamard transforms; binary sequences; block codes; channel coding; decoding; linear codes; rate distortion theory; source coding; vector quantisation; Hadamard transform; affine index assignments; analytic formulas; average distortion; binary lattice vector quantization; binary-symmetric channel; coding schemes; computationally efficient method; distortion formulas; encoder/decoder; linear block channel coding; linear block codes; low-complexity source-channel coding systems; natural binary code; nonredundant channel codes; nonsymmetric channel; optimal code; performance; structured index assignments; uniform quantizer; uniform source; vector mean-square error; Algorithm design and analysis; Binary codes; Block codes; Channel coding; Computational complexity; Decoding; Error correction codes; Lattices; Performance analysis; Vector quantization;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/18.650990
  • Filename
    650990