Full-Space Covert Integrated Sensing and Communications Assisted by Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surface

XIE Wenwu; ZHANG Qinke; YANG Liang; WANG Ji; YU Chao; LIU Xinzhong; CUI Yaru

doi:10.11999/JEIT260145

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XIE Wenwu, ZHANG Qinke, YANG Liang, WANG Ji, YU Chao, LIU Xinzhong, CUI Yaru. Full-Space Covert Integrated Sensing and Communications Assisted by Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surface[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260145

Citation:

XIE Wenwu, ZHANG Qinke, YANG Liang, WANG Ji, YU Chao, LIU Xinzhong, CUI Yaru. Full-Space Covert Integrated Sensing and Communications Assisted by Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surface[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260145

Citation:

XIE Wenwu, ZHANG Qinke, YANG Liang, WANG Ji, YU Chao, LIU Xinzhong, CUI Yaru. Full-Space Covert Integrated Sensing and Communications Assisted by Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surface[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT260145

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Full-Space Covert Integrated Sensing and Communications Assisted by Simultaneous Transmitting and Reflecting Reconfigurable Intelligent Surface

doi: 10.11999/JEIT260145 cstr: 32379.14.JEIT260145

1.
College of Information Science and Engineering, Hunan Institute of Science and Technology, Yueyang 414006, China
2.
College of Information Science and Engineering, Hunan University, Changsha 410082, China
3.
College of Physical Science and Technology, Central China Normal University, Wuhan 430079, China

Funds: The National Natural Science Foundation of China (62472169), Hunan Provincial Natural Science Foundation (2023JJ50045, 2024JJ7218, 2024JJ7219), The Project of Education Bureau of Hunan Province (22B0676, 23C0217), Hunan Provincial College Students Innovation and Entrepreneurship-Project: (S202410543061)

Received Date: 2026-02-14
Accepted Date: 2026-04-17
Rev Recd Date: 2026-04-14

Available Online: 2026-05-05

Abstract

Abstract

Objective The evolution of Sixth Generation (6G) mobile communications toward higher frequencies and larger antenna arrays has made Integrated Sensing And Communication (ISAC) a key enabling technology. However, ISAC systems still face limited communication covertness and resource competition between sensing and communication. Covert communication and Reconfigurable Intelligent Surface (RIS) techniques provide promising solutions. However, most existing studies use reflective RISs with half-space coverage and assume far-field propagation. These assumptions limit deployment flexibility and fail to capture near-field spherical-wave characteristics. To address these issues, this paper proposes a near-field full-space ISAC framework assisted by an Extremely Large-Scale Simultaneously Transmitting And Reflecting Reconfigurable Intelligent Surface (XL-STAR-RIS). The objective is to jointly optimize active transmit beamforming and passive XL-STAR-RIS coefficient design to improve the covert communication rate while satisfying sensing performance and covertness requirements. Methods The detection capability of warden Willie is first analyzed, and a closed-form lower-bound expression for the minimum Detection Error Probability (DEP) is derived. A non-convex optimization problem is then formulated to maximize the covert communication rate under sensing Signal-to-Noise Ratio (SNR), covertness, and total transmit power constraints. Direct solution is difficult because the active transmit beamforming vectors and passive XL-STAR-RIS coefficients are strongly coupled. An Alternating Optimization (AO) framework is therefore adopted to decompose the original problem into two tractable subproblems. The active transmit beamforming subproblem is solved using SemiDefinite Relaxation (SDR) combined with a penalty-based successive convex approximation method. The passive XL-STAR-RIS coefficient design subproblem is solved using the Dinkelbach algorithm and a rank-one penalty method. The two subproblems are solved alternately until convergence. Results and Discussions Simulation results verify the effectiveness of the proposed framework. The algorithm converges within approximately 10 iterations and achieves a covert communication rate of about 11.5 bit/(s·Hz). This rate is higher than those of the passive-RIS scheme (9.8 bit/(s·Hz)) and the non-RIS scheme (8.0 bit/(s·Hz)). The performance gain becomes more evident as the transmit power increases, which indicates strong power adaptability. The proposed framework also maintains robust performance under strict operational constraints. When the sensing SNR threshold increases, it achieves a higher covert communication rate than the benchmark schemes. Under a stricter covertness requirement, it also preserves a higher communication rate. These results show that joint active transmit beamforming and passive XL-STAR-RIS coefficient design can effectively balance communication, sensing, and covertness in near-field ISAC systems. Conclusions This paper presents an XL-STAR-RIS-assisted covert communication framework for near-field ISAC systems. By jointly designing active transmit beamforming and passive XL-STAR-RIS coefficients through an efficient AO algorithm, the proposed framework balances communication rate, sensing performance, and communication covertness. Simulation results confirm its advantages over conventional passive-RIS and non-RIS schemes, especially under strict sensing and covertness constraints. The results also indicate the potential of XL-STAR-RIS for secure full-space 6G applications. Future work will consider imperfect Channel State Information (CSI), dynamic propagation environments, and multi-RIS collaboration to improve practical robustness.

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References(17)

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