Resource Allocation for Green Probabilistic Semantic Communication with Rate Splitting

Fuente: arXiv
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Hauptverfasser: Xu, Ruopeng, Yang, Zhaohui, Zhao, Zhouxiang, Yang, Qianqian, Zhang, Zhaoyang
Format: Preprint
Veröffentlicht: 2024
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author Xu, Ruopeng
Yang, Zhaohui
Zhao, Zhouxiang
Yang, Qianqian
Zhang, Zhaoyang
author_facet Xu, Ruopeng
Yang, Zhaohui
Zhao, Zhouxiang
Yang, Qianqian
Zhang, Zhaoyang
contents In this paper, the energy efficient design for probabilistic semantic communication (PSC) system with rate splitting multiple access (RSMA) is investigated. Basic principles are first reviewed to show how the PSC system works to extract, compress and transmit the semantic information in a task-oriented transmission. Subsequently, the process of how multiuser semantic information can be represented, compressed and transmitted with RSMA is presented, during which the semantic compression ratio (SCR) is introduced to directly measure the computation overhead in a transmission task, and communication overhead is indirectly described as well. Hence, the problem of wireless resource allocation jointly considering the computation and communication consumption for the PSC system with RSMA is investigated. Both conventional wireless resource constraints and unique constraints on semantic communication are considered to maximize the energy efficiency (EE). Simulation results verify the effectiveness of the proposed scheme.
format Preprint
id arxiv_https___arxiv_org_abs_2404_00612
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Resource Allocation for Green Probabilistic Semantic Communication with Rate Splitting
Xu, Ruopeng
Yang, Zhaohui
Zhao, Zhouxiang
Yang, Qianqian
Zhang, Zhaoyang
Information Theory
Signal Processing
In this paper, the energy efficient design for probabilistic semantic communication (PSC) system with rate splitting multiple access (RSMA) is investigated. Basic principles are first reviewed to show how the PSC system works to extract, compress and transmit the semantic information in a task-oriented transmission. Subsequently, the process of how multiuser semantic information can be represented, compressed and transmitted with RSMA is presented, during which the semantic compression ratio (SCR) is introduced to directly measure the computation overhead in a transmission task, and communication overhead is indirectly described as well. Hence, the problem of wireless resource allocation jointly considering the computation and communication consumption for the PSC system with RSMA is investigated. Both conventional wireless resource constraints and unique constraints on semantic communication are considered to maximize the energy efficiency (EE). Simulation results verify the effectiveness of the proposed scheme.
title Resource Allocation for Green Probabilistic Semantic Communication with Rate Splitting
topic Information Theory
Signal Processing
url https://arxiv.org/abs/2404.00612