English

Maxflow-Based Bounds for Low-Rate Information Propagation over Noisy Networks

Information Theory 2023-04-06 v1 math.IT

Abstract

We study error exponents for the problem of low-rate communication over a directed graph, where each edge in the graph represents a noisy communication channel, and there is a single source and destination. We derive maxflow-based achievability and converse bounds on the error exponent that match when there are two messages and all channels satisfy a symmetry condition called pairwise reversibility. More generally, we show that the upper and lower bounds match to within a factor of 4. We also show that with three messages there are cases where the maxflow-based error exponent is strictly suboptimal, thus showing that our tightness result cannot be extended beyond two messages without further assumptions.

Keywords

Cite

@article{arxiv.2304.02226,
  title  = {Maxflow-Based Bounds for Low-Rate Information Propagation over Noisy Networks},
  author = {Yan Hao Ling and Jonathan Scarlett},
  journal= {arXiv preprint arXiv:2304.02226},
  year   = {2023}
}
R2 v1 2026-06-28T09:50:13.661Z