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cs.IT2026

A Gaussian Perspective for Distributional Discrepancy in Generative Diffusion Models

Qiang Sun, H. Vincent Poor, Wenyi Zhang

This paper introduces an analytical approach to quantifying and optimizing the distributional discrepancy in generative diffusion models. For a multivariate Gaussian source, we exp…

cs.IT2026

FDD CSI Feedback under Finite Downlink Training: A Rate-Distortion Perspective

Shuao Chen, Junyuan Gao, Yuxuan Shi +4

This paper establishes the theoretical limits of channel state information (CSI) feedback in frequency-division duplexing (FDD) multi-antenna orthogonal frequency-division multiple…

cs.IT2026

Joint Lossy Compression for a Vector Gaussian Source under Individual Distortion Criteria

Shuao Chen, Junyuan Gao, Yuxuan Shi +4

This paper investigates the joint compression problem of a vector Gaussian source, where an individual distortion constraint is imposed on each source component. It is known that t…

cs.IT2025

Finite-Blocklength Information Theory

Junyuan Gao, Shuao Chen, Yongpeng Wu +4

Traditional asymptotic information-theoretic studies of the fundamental limits of wireless communication systems primarily rely on some ideal assumptions, such as infinite blocklen…

cs.IT2024

A Rate-Distortion Analysis for Composite Sources Under Subsource-Dependent Fidelity Criteria

Jiakun Liu, H. Vincent Poor, Iickho Song +1

A composite source, consisting of multiple subsources and a memoryless switch, outputs one symbol at a time from the subsource selected by the switch. If some data should be encode…