智能超表面赋能语义通信系统研究综述

朱政宇; 梁馨月; 孙钢灿; 牛凯; 楚征; 杨照辉; 杨光睿; 郑谷寒

doi:10.11999/JEIT240984

智能超表面赋能语义通信系统研究综述

doi: 10.11999/JEIT240984

1.
郑州大学电气与信息工程学院郑州 450001
2.
北京邮电大学人工智能学院北京 100876
3.
宁波诺丁汉大学电气与电子工程系宁波 315100
4.
浙江大学电子与信息工程学院杭州 310058
5.
科学技术部新技术中心北京 100036
6.
兰卡斯特大学计算与通信学院英格兰 LA14YW

基金项目: 西安电子科技大学空天地一体化综合业务网全国重点实验室(ISN25-24)，河南省高校科技创新人才支持计划资助(23HASTIT019)，河南省自然科学基金优青项目(232300421097)

详细信息

作者简介:
朱政宇：男，副教授，研究方向为智能超表面、通感一体化、语义通信等

梁馨月：女，硕士生，研究方向为语义通信、生成式人工智能等

孙钢灿：男，教授，研究方向为宽带无线通信、智能物联网等

牛凯：男，教授，研究方向为下一代移动通信、移动云计算与数据挖掘等

楚征：男，教授，研究方向为智能超表面、人工智能驱动的未来网络等

杨照辉：男，教授，研究方向为语义通信、智能超表面等

杨光睿：男，助理研究员，研究方向为国家科技前沿领域技术监测等

郑谷寒：男，博士，研究方向为语义通信、深度学习等

通讯作者:
孙钢灿　iegcsun@zzu.edu.cn

中图分类号: TN915.0
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- 文章访问数: 8
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- 被引次数: 0
出版历程
- 收稿日期: 2024-11-04
- 修回日期: 2025-02-20
- 网络出版日期: 2025-02-24

Research Overview of Reconfigurable Intelligent Surface Enabled Semantic Communication Systems

1.
School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China
2.
School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China
3.
Department of Electrical and Electronics Engineering, University of Nottingham Ningbo China, Ningbo 315100, China
4.
School of Electronics and Information Engineering, Zhejiang University, Hangzhou 310058, China
5.
Innovative Technology Center, Most, Beijing 100036, China
6.
School of Computing and Communications, Lancaster University, Lancashire LA1 4YW, England

Funds: The Program for Science Technology Innovation Talents in Universities of Henan Province (23HASTIT019), The Natural Science Foundation of Henan Province (232300421097), The State Key Laboratory of Integrated Services Networks (ISN25-24, Xidian University)

摘要

摘要: 智能超表面(RIS)以其卓越的成本效益、低能耗及独特的可编程性，在调控无线环境方面展现出显著优势，已成为6G通信技术的关键组成部分。语义通信(SemCom)突破香农极限，同时确保关键信息的精确传递，同样被视为6G的核心技术之一。该文首先回顾了语义通信的发展历程，阐述其从理论走向实践的过程，并分析了RIS在提高通信性能方面的突出优势。接着，提出RIS赋能语义通信系统模型，展示了RIS在提升通信质量方面的显著效果。最后，对RIS赋能语义通信系统的未来发展趋势进行展望，其将迈向智能化、个性化信息传递新阶段，为6G通信技术发展奠定坚实基础，并有望成为6G核心关键技术，引导通信革命。
- 智能超表面 /
- 语义通信 /
- 无线通信 /
- 第六代移动通信
Abstract: Objective The proliferation of the sixth-Generation (6G) wireless networks technologies has catalyzed an exponential demand for intelligent devices, such as autonomous transportation, environmental monitoring and consumer robotics. These applications will generate a staggering amount of data in the order of zetta-bytes. Besides, these applications need to support massive connectivity over limited spectrum resources but require lower latency, which poses critical challenges to traditional source-channel coding. Consequently, the 6G architecture is transitioned from a traditional framework characterized by exclusive emphasis on high transmission rates to a novel paradigm centered on the intelligent interconnection of all things. Semantic Communication (SemCom) are believed to extend the Shannon communication paradigm by extracting the meanings of data and filtering out the useless, irrelevant, and unessential information in the semantic domain. As a new core paradigm in 6G, SemCom enhances transmission accuracy and spectral efficiency, thereby delivering optimized service quality to users. While semantic communication demonstrates significant potential to enhance transmission accuracy and spectral efficiency, thereby delivering superior quality-of-service as a prospective 6G paradigm, substantial challenges remain to be addressed. Reconfigurable Intelligent Surfaces (RIS), recognized as a pivotal enabler for 6G networks, can be dynamically deployed in wireless propagation environments to manipulate electromagnetic wave characteristics (e.g., frequency, phase, and polarization) through programmable reflection and refraction, thereby reshaping wireless channels to amplify signal strength, extend coverage, and optimize system performance. The integration of RIS into SemCom systems addresses critical limitations such as coverage voids while enhancing the precision and efficiency of semantic information delivery. This paper proposes an RIS enabled SemCom framework, with numerical simulations validating its effectiveness in improving system accuracy and robustness. Methods Based on the SemCom system, this paper introduces a RIS into the channel. The transmitted signal reaches the receiver through both the direct link and the RIS - reflected link, thereby mitigating communication interruptions caused by obstructions. Furthermore, the Bilingual Evaluation Understudy (BLEU) metric is adopted as the performance evaluation criterion. Simulation comparisons are conducted between RIS - enhanced channels and conventional channels (e.g., AWGN and Rayleigh channels), validating the performance gain of RIS in SemCom systems. Results and Discussions A positive correlation is observed between signal-to-noise ratio (SNR) increments and BLEU score improvements, where elevated BLEU score signify enhanced text reconstruction fidelity to source content, thereby indicating superior semantic accuracy and communication quality (Fig.4). Under RIS - enhanced channel conditions, SemCom systems demonstrate not only higher BLEU values but also greater stability, exhibiting reduced sensitivity to SNR fluctuations, which validates the exceptional advantages of RIS channels in semantic information recovery. Notably, the performance gap in BLEU values between RIS channels and conventional channels widens significantly under low SNR regimes, suggesting RIS - enabled systems maintain robust communication quality and semantic fidelity under signal degradation, thereby demonstrating stronger practical competitiveness. Furthermore, the comparative analysis in Figures 4(a) and (b) highlights performance divergences across N - gram models. Consequently, practical implementations necessitate model selection based on computational constraints and task requirements, with potential exploration of higher-order N - gram architectures. Conclusions This paper systematically investigates the evolutionary trajectory of SemCom and the foundational theoretical framework of RIS. SemCom, aiming to transcend the bandwidth limitations of conventional systems by enabling natural human-machine interactions, has demonstrated transformative potential across diverse domains. Concurrently, this paper analyzes RIS's inherent advantages in enhancing wireless system performance and its prospective integration with semantic communication paradigms. A novel RIS - enabled SemCom architecture is proposed, with experimental validation confirming its effectiveness in enhancing information recovery accuracy. Furthermore, this paper delineates prospective research directions for RIS - enhanced SemCom, calling for concerted efforts from the research community to address these emerging challenges. Prospects Current research on RIS - enabled SemCom remains nascent, primarily focusing on resource allocation, performance enhancement, and architectural design, while facing fundamental limitations including the absence of Shannon-like theoretical foundations and vulnerabilities in knowledge base synchronization and updating. Three critical challenges emerge: (1)Cross-modal semantic fusion architecture requiring adaptive frameworks to support diversified 6G services beyond single-modality paradigms; (2)Dynamic knowledge base optimization demanding efficient update mechanisms to balance semantic consistency with computational/communication overhead; (3)Semantic-aware security protocols needing hybrid defenses against AI-specific attacks (e.g., adversarial perturbations) and RIS - enabled channel manipulation threats.
- Reconfigurable Intelligent Surface /
- Semantic communication /
- Wireless communication /
- 6G

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图 1 语义通信架构

下载: 全尺寸图片幻灯片

图 2 RIS对无线信道的主要功能

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图 3 RIS赋能语义通信系统应用场景图

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图 4 不同信道条件下BLEU与SNR关系

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