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arxiv: 1508.04227 · v2 · pith:5KPGTPVQnew · submitted 2015-08-18 · 💻 cs.IT · math.IT

Second-Order Region for Gray-Wyner Network

classification 💻 cs.IT math.IT
keywords regionsecond-ordernetworkgray-wynerprovedcharacterizedcodingconverse
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The coding problem over the Gray-Wyner network is studied from the second-order coding rates perspective. A tilted information density for this network is introduced in the spirit of Kostina-Verd\'u, and, under a certain regularity condition, the second-order region is characterized in terms of the variance of this tilted information density and the tangent vector of the first-order region. The second-order region is proved by the type method: the achievability part is proved by the type-covering argument, and the converse part is proved by a refinement of the perturbation approach that was used by Gu-Effros to show the strong converse of the Gray-Wyner network. This is the first instance that the second-order region is characterized for a multi-terminal problem where the characterization of the first-order region involves an auxiliary random variable.

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