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arXiv 1508.03349cs.ITmath.IT
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多元覆盖引理及其逆定理

The Multivariate Covering Lemma and its Converse

Parham Noorzad, Michelle Effros, Michael Langberg

摘要:

多变量覆盖引理指出,给定$k$码本的集合,每个码本具有足够大的基数并且根据联合分布的边缘之一独立地生成,总是可以从每个码本选择一个码字,使得所得的码字的$k$元组相对于联合分布是联合典型的。我们给出了弱典型集的引理的一个证明。这允许依赖于覆盖引理的可扩展性证明通过连续通道(例如,高斯)而不需要量化。覆盖引理及其逆在信息论中有着广泛的应用,包括在率失真理论和多用户信道的可扩展性结果中。

英文摘要:

The multivariate covering lemma states that given a collection of $k$ codebooks, each of sufficiently large cardinality and independently generated according to one of the marginals of a joint distribution, one can always choose one codeword from each codebook such that the resulting $k$-tuple of codewords is jointly typical with respect to the joint distribution. We give a proof of this lemma for weakly typical sets. This allows achievability proofs that rely on the covering lemma to go through for continuous channels (e.g., Gaussian) without the need for quantization. The covering lemma and its converse are widely used in information theory, including in rate-distortion theory and in achievability results for multi-user channels.

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