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Lossless Source Coding with Marginal Distribution Constraint

  • Cheuk Ting Li
  • Jun Chen
  • Shahab Asoodeh
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Abstract

We consider lossless source coding with a marginal distribution constraint on the encoding symbols (SC-MDC). Unlike distribution matching, signal shaping and homophonic coding which require the symbols to be (approximately) i.i.d. following a target distribution, SC-MDC requires each symbol to have a marginal distribution that exactly matches the target distribution, which can be regarded as a perfect perceptual quality constraint on the symbols, and may have applications to wear leveling, source coding with cost and steganography. We give nonasymptotic lower and upper bounds on the optimal encoding length, and exactly characterize the coding rate (or the first-order term of the length) when the source distribution or the target distribution is uniform, or when the source is an i.i.d. sequence.

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Cite

BibTeXRIS
BibTeX
@misc{li2026lossless,
  title = {{Lossless Source Coding with Marginal Distribution Constraint}},
  author = {Cheuk Ting Li and Jun Chen and Shahab Asoodeh},
  howpublished = {arXiv},
  year = {2026},
  month = nov,
  doi = {10.48550/arxiv.2611.07156},
  eprint = {2611.07156},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2611.07156},
}
RIS
TY  - UNPB
TI  - Lossless Source Coding with Marginal Distribution Constraint
AU  - Cheuk Ting Li
AU  - Jun Chen
AU  - Shahab Asoodeh
PY  - 2026
DA  - 2026/11/04
PB  - arXiv
DO  - 10.48550/arxiv.2611.07156
UR  - https://arxiv.org/abs/2611.07156
AB  - We consider lossless source coding with a marginal distribution constraint on the encoding symbols (SC-MDC). Unlike distribution matching, signal shaping and homophonic coding which require the symbols to be (approximately) i.i.d. following a target distribution, SC-MDC requires each symbol to have a marginal distribution that exactly matches the target distribution, which can be regarded as a perfect perceptual quality constraint on the symbols, and may have applications to wear leveling, source coding with cost and steganography. We give nonasymptotic lower and upper bounds on the optimal encoding length, and exactly characterize the coding rate (or the first-order term of the length) when the source distribution or the target distribution is uniform, or when the source is an i.i.d. sequence.
ER  -