基于同时透射与反射可重构智能表面的通感一体化全空间隐蔽传输

谢文武; 张沁可; 杨亮; 王骥; 余超; 刘新忠; 崔亚茹

doi:10.11999/JEIT260145

基于同时透射与反射可重构智能表面的通感一体化全空间隐蔽传输

doi: 10.11999/JEIT260145 cstr: 32379.14.JEIT260145

1.
湖南理工大学信息科学与工程学院岳阳 414006
2.
湖南大学计算机学院长沙 410082
3.
华中师范大学物理科学与技术学院武汉 430079

基金项目: 国家自然科学基金(62472169)，湖南省自然科学基金(2023JJ50045, 2024JJ7218, 2024JJ7219)，湖南省教育厅项目(22B0676, 23C0217)，湖南省大学生创新创业项目(S202410543061)

详细信息

作者简介:
谢文武：男，副教授，研究方向为5G&6G基带算法、NFC等

张沁可：女，硕士生，研究方向为RIS、凸优化

杨亮：男，教授，研究方向为可重构智能表面、非正交多址接入等

王骥：男，副教授，研究方向为5G/6G无线通信

余超：男，副教授，研究方向为NOMA、凸优化

刘新忠：男，副教授，研究方向为边缘计算、信息安全、汽车电子等

崔亚茹：女，本科生，研究方向为可重构智能表面

通讯作者:
余超　12012017@hnist.edu.cn

中图分类号: TN929.5
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- 被引次数: 0
出版历程
- 收稿日期: 2026-02-14
- 修回日期: 2026-04-14
- 录用日期: 2026-04-17
- 网络出版日期: 2026-05-05

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

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)

摘要

摘要: 为提高通感一体化(ISAC)系统中信息传输的隐蔽性，该文研究基于超大规模同时透射与反射可重构智能表面(XL-STAR-RIS)辅助的近场通感一体化系统，旨在实现隐蔽通信的资源优化。首先，建立近场球面波信道模型与信号传输模型，分析窃听者Willie的最优检测性能，并推导其最小检测错误概率的闭合下界表达式。在此基础上，根据通信要求，以最大化隐蔽通信速率为目标，综合考虑发射功率约束、感知信噪比约束及隐蔽性要求，构建了联合波束成形优化问题。为解决该非凸问题，该文提出一种融合半定松弛(SDR)、Dinkelbach型迭代与惩罚函数的分层交替优化算法，实现了主动发射波束与被动STAR-RIS系数的协同设计。仿真结果表明，所提方案在隐蔽通信速率、感知精度与收敛性能方面均优于传统被动RIS及无RIS基准方案。
- 隐蔽通信 /
- 超大规模同时透射与反射可重构智能表面 /
- 通感一体化
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.

HTML全文

图 1 XL-STAR-RIS辅助的近场隐蔽通信系统

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图 2 通信速率与迭代次数的关系

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图 3 隐蔽通信速率与$ {P}_{\max } $的关系

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图 4 隐蔽通信速率与雷达感知需求阈值的关系

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图 5 隐蔽通信速率与隐蔽需求阈值的关系

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表 1 仿真参数

参数	符号和数值	单位
波长	$ \lambda =0.03 $	m
天线间距	$ d=\dfrac{\lambda }{2} $	m
1 m处的路径损耗	$ {\rho }_{0}=30 $	dB
总传输功率	$ {P}_{\max }=30 $	dB
噪声功率	$ {\sigma }^{2}=-85 $	dB
莱斯因子	$ \varepsilon =3 $	dB
路径损耗指数	$ {\alpha }_{\text{br}}=2 $

下载: 导出CSV

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