面向带宽受限场景的高效语义通信方法

刘伟; 王孟洋; 白宝明

doi:10.19665/j.issn1001-2400.20240203

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面向带宽受限场景的高效语义通信方法

信息与通信工程 | 更新时间：2024-07-23

- 面向带宽受限场景的高效语义通信方法
- Efficient semantic communication method for bandwidth constrained scenarios
- 西安电子科技大学学报 2024年51卷第3期页码：9-18
- 作者机构：
  
  西安电子科技大学通信工程学院,陕西西安 710071
- 作者简介：
  
  [ "刘伟(1977—),男,教授,博士,E-mail:[email protected]" ]
  [ "王孟洋(1998—),男,西安电子科技大学硕士研究生,E-mail:[email protected]" ]
  [ "白宝明(1966—),男,教授,博士,E-mail:[email protected]" ]
- 基金信息：
  
  国家重点研发计划(2021YFA1000500);陕西省重点研发计划项目(2022ZDLGY05-05)
- DOI：10.19665/j.issn1001-2400.20240203
  中图分类号： TN911.22
- 纸质出版日期：2024-06-20，
  
  网络出版日期：2024-03-13，
  
  收稿日期：2023-06-16，
- 稿件说明：
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刘伟, 王孟洋, 白宝明. 面向带宽受限场景的高效语义通信方法[J]. 西安电子科技大学学报, 2024,51(3):9-18.

Wei LIU, Mengyang WANG, Baoming BAI. Efficient semantic communication method for bandwidth constrained scenarios[J]. Journal of Xidian University, 2024,51(3):9-18.
刘伟, 王孟洋, 白宝明. 面向带宽受限场景的高效语义通信方法[J]. 西安电子科技大学学报, 2024,51(3):9-18. DOI： 10.19665/j.issn1001-2400.20240203.

Wei LIU, Mengyang WANG, Baoming BAI. Efficient semantic communication method for bandwidth constrained scenarios[J]. Journal of Xidian University, 2024,51(3):9-18. DOI： 10.19665/j.issn1001-2400.20240203.

摘要

语义通信为通信系统优化和性能提升提供了新的研究角度

然而

目前语义通信的研究忽略了通信开销的影响

未考虑语义通信性能和通信开销的关系

导致带宽资源受限时语义通信性能难以提升。为此

针对带宽受限场景

提出一种基于信息瓶颈的语义通信方法。首先

该方法采用Transformer模型进行语义和信道联合编解码

并设计特征选择模块以识别和删除冗余语义信息

构建了端到端语义通信模型;进而考虑语义通信性能与通信开销之间的折衷关系

基于信息瓶颈理论设计损失函数

在保证语义通信性能的同时

降低通信开销

完成语义通信模型的训练和优化。实验结果显示

在欧洲议会平行语料库上

与基线模型相比

所提方法在保证通信性能的同时可降低约20%~30%的通信开销

在相同带宽条件下该方法的BLEU分数可提升约5%。实验结果表明

所提方法可以有效降低语义通信开销

从而提升带宽资源受限场景下的语义通信性能。

Abstract

Semantic communication provides a new research perspective for communication system optimization and performance improvement.However

current research on semantic communication ignores the impact of communication overhead and does not consider the relationship between semantic communication performance and communication overhead

resulting in difficulty in improving semantic communication performance when the bandwidth resource is limited.Therefore

an information bottleneck based semantic communication method for text sources is proposed.First

the Transformer model is used for semantic and channel joint encoding and decoding

and a feature selection module is designed to identify and delete redundant information

and then an end-to-end semantic communication model is constructed in the method;Second

considering the tradeoff between semantic communication performance and communication cost

a loss function is designed based on the information bottleneck theory to ensure the semantic communication performance

reduce the communication cost

and complete the training and optimization of the semantic communication model.Experimental results show that on the proceedings of the European Parliament

compared with the baseline model

the proposed method can reduce communication overhead by 20%~30% while ensuring communication performance.Under the same bandwidth conditions

the BLEU score of this method can be increased by 5%.Experimental results prove that the proposed method can effectively reduce the semantic communication overhead

thereby improving semantic communication performance when the bandwidth resource is limited.

关键词

语义通信通信系统深度学习Transformer特征选择模块信息瓶颈理论

Keywords

semantic communicationcommunication systemsdeep learningtransformerfeature selection moduleinformation bottleneck theory

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