Knowledge-Aided Semantic Communication Leveraging Probabilistic Graphical Modeling

Fuente: arXiv
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Main Authors: Wan, Haowen, Yang, Qianqian, Tang, Jiancheng, shi, Zhiguo
Format: Preprint
Published: 2024
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author Wan, Haowen
Yang, Qianqian
Tang, Jiancheng
shi, Zhiguo
author_facet Wan, Haowen
Yang, Qianqian
Tang, Jiancheng
shi, Zhiguo
contents In this paper, we propose a semantic communication approach based on probabilistic graphical model (PGM). The proposed approach involves constructing a PGM from a training dataset, which is then shared as common knowledge between the transmitter and receiver. We evaluate the importance of various semantic features and present a PGM-based compression algorithm designed to eliminate predictable portions of semantic information. Furthermore, we introduce a technique to reconstruct the discarded semantic information at the receiver end, generating approximate results based on the PGM. Simulation results indicate a significant improvement in transmission efficiency over existing methods, while maintaining the quality of the transmitted images.
format Preprint
id arxiv_https___arxiv_org_abs_2408_04499
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Knowledge-Aided Semantic Communication Leveraging Probabilistic Graphical Modeling
Wan, Haowen
Yang, Qianqian
Tang, Jiancheng
shi, Zhiguo
Machine Learning
In this paper, we propose a semantic communication approach based on probabilistic graphical model (PGM). The proposed approach involves constructing a PGM from a training dataset, which is then shared as common knowledge between the transmitter and receiver. We evaluate the importance of various semantic features and present a PGM-based compression algorithm designed to eliminate predictable portions of semantic information. Furthermore, we introduce a technique to reconstruct the discarded semantic information at the receiver end, generating approximate results based on the PGM. Simulation results indicate a significant improvement in transmission efficiency over existing methods, while maintaining the quality of the transmitted images.
title Knowledge-Aided Semantic Communication Leveraging Probabilistic Graphical Modeling
topic Machine Learning
url https://arxiv.org/abs/2408.04499