Year: 2025
Type: article
Abstract: Motivated by task-oriented semantic communication and distributed learning systems, this paper studies a distributed indirect source coding problem where M correlated sources are independently encoded for a central decoder. The decoder has access to correlated side information in addition to the messages received from the encoders and aims to recover a latent random variable under a given distortion constraint rather than recovering the sources themselves. We characterize the exact rate-distortion function for the case where the sources are conditionally independent given the side information. Furthermore, we develop a distributed Blahut–Arimoto (BA) algorithm to numerically compute the rate-distortion function. Numerical examples are provided to demonstrate the effectiveness of the proposed approach in calculating the rate-distortion region.
Source: Entropy
DOI: 10.3390/e27080844
Authors: Jiancheng Tang, Qianqian Yang
Institution: Zhejiang University
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Awards: G1937424723, G4710423954, G6454029087
OpenAlex ID: W4413121744