One-Shot Coding over General Noisy Networks
CoRR(2024)
摘要
We present a unified one-shot coding framework designed for communication and
compression of messages among multiple nodes across a general acyclic noisy
network. Our setting can be seen as a one-shot version of the acyclic discrete
memoryless network studied by Lee and Chung, and noisy network coding studied
by Lim, Kim, El Gamal and Chung. We design a proof technique, called the
exponential process refinement lemma, that is rooted in the Poisson matching
lemma by Li and Anantharam, and can significantly simplify the analyses of
one-shot coding over multi-hop networks. Our one-shot coding theorem not only
recovers a wide range of existing asymptotic results, but also yields novel
one-shot achievability results in different multi-hop network information
theory problems. In a broader context, our framework provides a unified
one-shot bound applicable to any combination of source coding, channel coding
and coding for computing problems.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要