智能超表面賦能語義通信系統(tǒng)研究綜述

朱政宇; 梁馨月; 孫鋼燦; 牛凱; 楚征; 楊照輝; 楊光睿; 鄭谷寒

doi:10.11999/JEIT240984

智能超表面賦能語義通信系統(tǒng)研究綜述

doi: 10.11999/JEIT240984 cstr: 32379.14.JEIT240984

1.
鄭州大學電氣與信息工程學院鄭州 450001
2.
北京郵電大學人工智能學院北京 100876
3.
寧波諾丁漢大學電氣與電子工程系寧波 315100
4.
浙江大學電子與信息工程學院杭州 310058
5.
科學技術部新技術中心北京 100036
6.
蘭卡斯特大學計算與通信學院英格蘭 LA14YW

基金項目: 西安電子科技大學空天地一體化綜合業(yè)務網(wǎng)全國重點實驗室(ISN25-24)，河南省高?？萍紕?chuàng)新人才支持計劃資助(23HASTIT019)，河南省自然科學基金優(yōu)青項目(232300421097)，寧波市自然科學基金資助項目(2024J233)

詳細信息

作者簡介:
朱政宇：男，副教授，研究方向為智能超表面、通感一體化、語義通信等

梁馨月：女，碩士生，研究方向為語義通信、生成式人工智能等

孫鋼燦：男，教授，研究方向為寬帶無線通信、智能物聯(lián)網(wǎng)等

牛凱：男，教授，研究方向為下一代移動通信、移動云計算與數(shù)據(jù)挖掘等

楚征：男，教授，研究方向為智能超表面、人工智能驅動的未來網(wǎng)絡等

楊照輝：男，教授，研究方向為語義通信、智能超表面等

楊光睿：男，助理研究員，研究方向為國家科技前沿領域技術監(jiān)測等

鄭谷寒：男，博士，研究方向為語義通信、深度學習等

通訊作者:
孫鋼燦　iegcsun@zzu.edu.cn

中圖分類號: TN915.0
計量
- 文章訪問數(shù): 536
- HTML全文瀏覽量: 166
- PDF下載量: 90
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2024-11-04
- 修回日期: 2025-02-20
- 網(wǎng)絡出版日期: 2025-02-24
- 刊出日期: 2025-02-28

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 State Key Laboratory for Excellent Young Scholars of Integrated Services Networks (ISN25-24, Xidian University), Ningbo Natural Science Foundation (2024J233), The Program for Science Technology Innovation Talents in Universities of Henan Province (23HASTIT019), The Natural Science Foundation of Henan Province (232300421097)

摘要

摘要: 智能超表面(RIS)以其卓越的成本效益、低能耗及獨特的可編程性，在調控無線環(huán)境方面展現(xiàn)出顯著優(yōu)勢，已成為6G通信技術的關鍵組成部分。語義通信(SemCom)突破香農極限，同時確保關鍵信息的精確傳遞，同樣被視為6G的核心技術之一。該文首先回顧了語義通信的發(fā)展歷程，闡述其從理論走向實踐的過程，并分析了RIS在提高通信性能方面的突出優(yōu)勢。接著，提出RIS賦能語義通信系統(tǒng)模型，展示了RIS在提升通信質量方面的顯著效果。最后，對RIS賦能語義通信系統(tǒng)的未來發(fā)展趨勢進行展望，其將邁向智能化、個性化信息傳遞新階段，為6G通信技術發(fā)展奠定堅實基礎，并有望成為6G核心關鍵技術，引導通信革命。
- 智能超表面 /
- 語義通信 /
- 無線通信 /
- 第六代移動通信
Abstract: Objective The proliferation of sixth-Generation (6G) wireless network technologies has led to an exponential demand for intelligent devices, such as autonomous transportation, environmental monitoring, and consumer robotics. These applications will generate vast amounts of data, reaching zetta-bytes in scale. Furthermore, they require support for massive connectivity over limited spectrum resources, and low latency, presenting critical challenges to traditional source-channel coding methods. Therefore, the 6G architecture is shifting from a traditional framework focused on high transmission rates to a novel paradigm centered on the intelligent interconnection of all things. Semantic Communication (SemCom) is considered an extension of the Shannon communication paradigm, aiming to extract the meaning from data and filter out unnecessary, irrelevant, or unessential information. As a core paradigm in 6G, SemCom enhances transmission accuracy and spectral efficiency, optimizing service quality. Despite its significant potential, challenges remain in implementing SemCom systems. Reconfigurable Intelligent Surfaces (RIS) are seen as key enablers for 6G networks. RIS can be dynamically deployed in wireless environments to manipulate electromagnetic wave characteristics (such as frequency, phase, and polarization) via programmable reflection and refraction, reshaping wireless channels to amplify signal strength, extend coverage, and optimize performance. Integrating RIS into SemCom systems helps address limitations like 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 This paper integrates RIS into the SemCom system. The transmitted signal reaches the receiver through both the direct link and the RIS-reflected link, mitigating communication interruptions caused by obstructions. Additionally, the Bilingual Evaluation Understudy (BLEU) metric is used to evaluate performance. Simulations compare RIS-enhanced channels with conventional channels (e.g., AWGN and Rayleigh), demonstrating the performance gain of RIS in SemCom systems. Results and Discussions A positive correlation is observed between Signal-To-Noise Ratio (SNR) increases and improvements in the BLEU score, where higher BLEU scores indicate better text reconstruction fidelity to the source content, reflecting enhanced semantic accuracy and communication quality (Fig. 4). Under RIS-enhanced channel conditions, SemCom systems not only show higher BLEU scores but also exhibit greater stability, with reduced sensitivity to SNR fluctuations. This validates the advantages of RIS channels in semantic information recovery. The performance gap between RIS and conventional channels widens significantly under low SNR conditions, suggesting that RIS-enabled systems maintain robust communication quality and semantic fidelity even with signal degradation, highlighting their stronger practical competitiveness. Additionally, the comparative analysis shows performance differences across N-gram models (Figs. 4(a) and (b)). Practical implementations, therefore, require model selection based on computational constraints and task requirements, with potential for exploring higher-order N-gram architectures. Conclusions This paper systematically examines the evolution of SemCom and the theoretical foundations of RIS. SemCom, aimed at overcoming the bandwidth limitations of traditional systems and enabling natural human-machine interactions, has shown transformative potential across various domains. At the same time, the paper highlights RIS’s advantages in improving wireless system performance and its potential integration with SemCom paradigms. A novel RIS-enabled SemCom architecture is proposed, with experimental validation confirming its effectiveness in enhancing information recovery accuracy. Additionally, the paper outlines future research directions for RIS-enhanced SemCom, urging the research community to address emerging challenges. Prospects Current research on RIS-enabled SemCom is still in its early stages, primarily focusing on resource allocation, performance enhancement, and architectural design. However, it faces fundamental challenges, such as the lack of Shannon-like theoretical foundations and vulnerabilities in knowledge base synchronization and updating. Three critical challenges emerge: (1) Cross-modal semantic fusion architecture, which requires adaptive frameworks to support diverse 6G services beyond single-modality paradigms; (2) Dynamic knowledge base optimization, requiring efficient update mechanisms to balance semantic consistency with computational and communication overhead; (3) Semantic-aware security protocols, which must incorporate hybrid defenses against AI-specific attacks (e.g., adversarial perturbations) and RIS-enabled channel manipulation threats.
- Reconfigurable Intelligent Surface (RIS) /
- Semantic communication /
- Wireless communication /
- 6G

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圖 1 語義通信架構

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圖 2 RIS對無線信道的主要功能

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圖 3 RIS賦能語義通信系統(tǒng)應用場景圖

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圖 4 不同信道條件下BLEU與SNR關系

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