Research Overview of Reconfigurable Intelligent Surface Enabled Semantic Communication Systems

ZHU Zhengyu; LIANG Xinyue; SUN Gangcan; NIU Kai; CHU Zheng; YANG Zhaohui; YANG Guangrui; ZHENG Guhan

doi:10.11999/JEIT240984

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ZHU Zhengyu, LIANG Xinyue, SUN Gangcan, NIU Kai, CHU Zheng, YANG Zhaohui, YANG Guangrui, ZHENG Guhan. Research Overview of Reconfigurable Intelligent Surface Enabled Semantic Communication Systems[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240984

Citation:

ZHU Zhengyu, LIANG Xinyue, SUN Gangcan, NIU Kai, CHU Zheng, YANG Zhaohui, YANG Guangrui, ZHENG Guhan. Research Overview of Reconfigurable Intelligent Surface Enabled Semantic Communication Systems[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240984

Citation:

ZHU Zhengyu, LIANG Xinyue, SUN Gangcan, NIU Kai, CHU Zheng, YANG Zhaohui, YANG Guangrui, ZHENG Guhan. Research Overview of Reconfigurable Intelligent Surface Enabled Semantic Communication Systems[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240984

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Research Overview of Reconfigurable Intelligent Surface Enabled Semantic Communication Systems

doi: 10.11999/JEIT240984

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)

Received Date: 2024-11-04
Rev Recd Date: 2025-02-20

Available Online: 2025-02-24

Abstract

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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References(27)

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