Strong Converse Exponent for Remote Lossy Source Coding
Information Theory
2025-04-24 v2 math.IT
Abstract
Past works on remote lossy source coding studied the rate under average distortion and the error exponent of excess distortion probability. In this work, we look into how fast the excess distortion probability converges to 1 at small rates, also known as exponential strong converse. We characterize its exponent by establishing matched upper and lower bounds. From the exponent, we also recover two previous results on lossy source coding and biometric authentication.
Cite
@article{arxiv.2501.14620,
title = {Strong Converse Exponent for Remote Lossy Source Coding},
author = {Han Wu and Hamdi Joudeh},
journal= {arXiv preprint arXiv:2501.14620},
year = {2025}
}
Comments
Accepted for presentation at 2025 IEEE International Symposium on Information Theory (ISIT)