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A Generalization of the DMC.

Sergey Tridenski1, Anelia Somekh-Baruch1

  • 1Faculty of Engineering, Bar-Ilan University, Ramat Gan 5290002, Israel.

Entropy (Basel, Switzerland)
|February 27, 2026
PubMed
Summary
This summary is machine-generated.

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This study introduces a generalized discrete memoryless channel model. We derived achievable error and decoding exponents, and channel ensemble capacity for random channel ensembles.

Area of Science:

  • Information Theory
  • Communication Systems

Background:

  • The discrete memoryless channel is a fundamental model in information theory.
  • Generalizations are needed to capture more complex channel behaviors.

Purpose of the Study:

  • To introduce and analyze a generalized discrete memoryless channel model.
  • To derive key performance metrics for this new channel model.

Main Methods:

  • Considered a generalization where channel distributions are uniform over clouds of output sequences.
  • Analyzed a random ensemble of these generalized channels.
  • Derived achievable and converse error exponents as functions of information rate.

Main Results:

  • Derived an achievable error exponent for the generalized channel.
Keywords:
correct-decodingdiscrete memoryless channel capacityerror exponent

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  • Obtained the converse and optimal correct-decoding exponent.
  • Established the channel ensemble capacity as a corollary.

    • Conclusions:

    • The derived exponents provide bounds on reliable communication rates.
    • The channel ensemble capacity quantifies the performance limit of the generalized channel model.