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PreprintCC BY 4.0arXiv

Entropy and Distributed Source Coding of Connected Soft Random Geometric Graphs

  • Oliver Baker
  • Carl P. Dettmann
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Abstract

We consider the distributed compression of Soft Random Geometric Graphs (SRGGs) above the connectivity threshold. We establish the Slepian-Wolf rate region for the SRGG in the setting where there are a finite number of encoders compressing sections of the graph independently. To do so, we prove novel limit theorems and asymptotic equipartition properties for the SRGG and its entropy, which allow us to use random binning techniques for distributed compression.

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Cite

BibTeXRIS
BibTeX
@misc{baker2026entropy,
  title = {{Entropy and Distributed Source Coding of Connected Soft Random Geometric Graphs}},
  author = {Oliver Baker and Carl P. Dettmann},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2605.04703},
  eprint = {2605.04703},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.04703},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Entropy and Distributed Source Coding of Connected Soft Random Geometric Graphs
AU  - Oliver Baker
AU  - Carl P. Dettmann
PY  - 2026
DA  - 2026/09/03
PB  - arXiv
DO  - 10.48550/arxiv.2605.04703
UR  - https://arxiv.org/abs/2605.04703
AB  - We consider the distributed compression of Soft Random Geometric Graphs (SRGGs) above the connectivity threshold. We establish the Slepian-Wolf rate region for the SRGG in the setting where there are a finite number of encoders compressing sections of the graph independently. To do so, we prove novel limit theorems and asymptotic equipartition properties for the SRGG and its entropy, which allow us to use random binning techniques for distributed compression.
ER  -