论文标题
高斯来源的常见随机性产生
Common Randomness Generation from Gaussian Sources
论文作者
论文摘要
我们研究了基本的两党通信环境中常见的随机性（CR）产生的问题，在该设置中，发件人和接收器的目的是通过观察独立和相同分布的高斯源样本和相关的高斯来源的样本，并在不可记忆的无内存频道上进行沟通，以高概率同意具有很高概率的常见随机变量。我们通过对提议模型的CR容量进行单个字母的表征，并提供严格的证明，从而完全解决了问题。有趣的是，我们证明当高斯源完全相关时，CR的容量是无限的。
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.
