| Paper ID | D6-S7-T2.1 |
| Paper Title |
Achievable Second-Order Asymptotics for Successive Refinement Using Gaussian Codebooks |
| Authors |
Lin Bai, Zhuangfei Wu, Lin Zhou, Beihang University, China |
| Session |
D6-S7-T2: Rate-Distortion Theory III |
| Chaired Session: |
Tuesday, 20 July, 00:00 - 00:20 |
| Engagement Session: |
Tuesday, 20 July, 00:20 - 00:40 |
| Abstract |
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 an 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.
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