One-shot Multiple Access Channel Simulation
Aditya Nema, Sreejith Sreekumar, Mario Berta

TL;DR
This paper characterizes the one-shot communication cost for shared randomness-assisted MAC simulation with product inputs, providing bounds, algorithms, and extending results to asymptotic and quantum settings.
Contribution
It introduces a new one-shot characterization of MAC simulation costs using smooth max-information, with bounds, algorithms, and quantum extensions.
Findings
Inner and outer bounds for one-shot MAC simulation costs
A rejection-sampling algorithm for auxiliary channel simulation
Extension of results to asymptotic and quantum scenarios
Abstract
We consider the problem of shared randomness-assisted multiple access channel (MAC) simulation for product inputs and characterize the one-shot communication cost region via almost-matching inner and outer bounds in terms of the smooth max-information of the channel, featuring auxiliary random variables of bounded size. The achievability relies on a rejection-sampling algorithm to simulate an auxiliary channel between each sender and the decoder, and producing the final output based on the output of these intermediate channels. The converse follows via information-spectrum based arguments. To bound the cardinality of the auxiliary random variables, we employ the perturbation method from [Anantharam et al., IEEE Trans. Inf. Theory (2019)] in the one-shot setting. For the asymptotic setting and vanishing errors, our result expands to a tight single-letter rate characterization and…
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