One-Shot Coding over General Noisy Networks
<|reference_start|>One-Shot Coding over General Noisy Networks: 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.<|reference_end|>
@article{liu2024one-shot,
    title={One-Shot Coding over General Noisy Networks},
    author={Yanxiao Liu and Cheuk Ting Li},
    journal={arXiv preprint arXiv:2402.06021},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.06021},
    primaryClass={cs.IT math.IT}
}