Refined Asymptotics for Rate-Distortion using Gaussian Codebooks for Arbitrary Sources
Lin Zhou, Vincent Y. F. Tan, Mehul Motani

TL;DR
This paper extends Lapidoth's analysis of Gaussian codebook rate-distortion problems by deriving refined asymptotics, excess-distortion exponents, and comparing spherical and i.i.d. Gaussian codebooks for arbitrary sources.
Contribution
It provides the second-order, moderate, and large deviation asymptotics for Gaussian codebooks, and compares the performance of spherical and i.i.d. Gaussian codebooks in rate-distortion.
Findings
Dispersions are identical for spherical and i.i.d. Gaussian codebooks.
i.i.d. Gaussian codebooks have larger excess-distortion exponents than spherical ones.
Refined asymptotics are established for stationary, memoryless sources.
Abstract
The rate-distortion saddle-point problem considered by Lapidoth (1997) consists in finding the minimum rate to compress an arbitrary ergodic source when one is constrained to use a random Gaussian codebook and minimum (Euclidean) distance encoding is employed. We extend Lapidoth's analysis in several directions in this paper. Firstly, we consider refined asymptotics. In particular, when the source is stationary and memoryless, we establish the second-order, moderate, and large deviation asymptotics of the problem. Secondly, by "random Gaussian codebook", Lapidoth referred to a collection of random codewords, each of which is drawn independently and uniformly from the surface of an -dimensional sphere. To be more precise, we term this as a spherical codebook. We also consider i.i.d.\ Gaussian codebooks in which each random codeword is drawn independently from a product Gaussian…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsWireless Communication Security Techniques · Cooperative Communication and Network Coding · Advanced Data Compression Techniques
