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RIS-enhanced Semantic-aware Sensing, Communication, Computation and Control for Internet of Things
Sichuan Normal University, College of Computer Science, Chengdu, China; Nanyang Technological University, School of Electrical and Electronic Engineering, Singapore.ORCID iD: 0000-0002-9911-8484
Nanyang Technological University, School of Electrical and Electronic Engineering, Singapore.ORCID iD: 0000-0002-9307-2120
Xidian University, Guangzhou Institute of Technology, Guangzhou, China.ORCID iD: 0000-0001-8173-0408
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.ORCID iD: 0000-0002-5407-0835
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2026 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 25, p. 2231-2246Article in journal (Refereed) Published
Abstract [en]

The joint design of sensing, communication, computing, and control (SC3) is crucial for supporting environment-aware Industrial Internet of Things (IIoT) applications. Considering the uncontrollable wireless propagation environments and limited spectrum resources, wireless communication performance often becomes the primary design bottleneck for such an integrated system. To address this challenge, this paper presents a design framework for reconfigurable intelligent surface (RIS)-enhanced semantic-aware SC3 networks, where RIS and semantic communication technologies are employed to improve wireless communication efficiency. To facilitate real-time closed-loop control, we further formulate a weighted sum execution latency minimization problem, while imposing constraints on maximum execution latency and energy consumption of individual IoT device, as well as minimum information entropy to meet specific control requirements measured by linear quadratic regulator cost. In addition, the design framework aims at optimizing bandwidth allocation, RIS phase shift matrix, time scheduling, transmit power, and CPU-cycle frequency for IoT devices and the base station (BS). To handle the coupled multi-dimensional optimization variables, the block coordinate descent method is utilized to decompose the formulated problem into more tractable subproblems, which are then solved using a penalty-function-based approach and geometric programming technique. Simulation results demonstrate the performance advantages achieved by our proposed method compared to several benchmark approaches. Additionally, we explore the impact of various parameters on SC3systems, offering deeper insights and meaningful research observations.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2026. Vol. 25, p. 2231-2246
Keywords [en]
reconfigurable intelligent surface, semantic communication, Sensing-communication-computing-control
National Category
Communication Systems Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-369351DOI: 10.1109/TWC.2025.3595550ISI: 001659565500018Scopus ID: 2-s2.0-105013385686OAI: oai:DiVA.org:kth-369351DiVA, id: diva2:1995096
Note

QC 20260127

Available from: 2025-09-04 Created: 2025-09-04 Last updated: 2026-05-29Bibliographically approved

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Xiao, Ming

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