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arXiv · 2201.11078

Common Randomness Generation from Gaussian Sources

Wafa Labidi·Rami Ezzine·Christian Deppe·Holger Boche
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Abstract

We study the problem of common randomness (CR) generation in the basic two-party communication setting in which the sender and the receiver aim to agree on a common random variable with high probability by observing independent and identically distributed (i.i.d.) samples of correlated Gaussian sources and while communicating as little as possible over a noisy memoryless channel. We completely solve the problem by giving a single-letter characterization of the CR capacity for the proposed model and by providing a rigorous proof of it. Interestingly, we prove that the CR capacity is infinite when the Gaussian sources are perfectly correlated.

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Wafa Labidi, Rami Ezzine, Christian Deppe, Holger Boche. 2022-01-26. Common Randomness Generation from Gaussian Sources. https://arxiv.org/abs/2201.11078

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