Achievable second-order asymptotics for successive refinement using Gaussian codebooks
作者：白琳 时间：2021年09月01日 08:17 点击数：
语言：English
发表会议：2021 IEEE International Symposium on Information Theory (ISIT)
发表日期：2021年9月1日
摘要：
We study the mismatched successive refinement problem where one uses a fixed code to compress an arbitrary source with random Gaussian codebooks and minimum Euclidean distance encoding in a successive manner. Specifically, we generalize the mismatched rate-distortion framework by Lapidoth (T-IT, 1997) to the successive refinement setting and derive the achievable second-order asymptotics. Our result implies that any source that satisfies a mild moment constraint is successive refinable under our code. Furthermore, our proof, when specialized to a Gaussian memoryless source, provides an alternative achievability proof with structured codebooks for the successive refinement problem, which was studied by Zhou, Tan, Motani (T-IT, 2018) where a covering lemma without specifying the locations of codewords was used.
原文链接
