具有可移动阵元的同时透射和反射可重构智能超表面辅助隐蔽通感一体系统：联合主动和柔性被动波束成形优化

周涛; 许魁; 夏晓晨; 胡国杰; 李春国; 谢威

doi:10.11999/JEIT240601

具有可移动阵元的同时透射和反射可重构智能超表面辅助隐蔽通感一体系统：联合主动和柔性被动波束成形优化

doi: 10.11999/JEIT240601

周涛¹,
许魁^1, ,,
夏晓晨¹,
胡国杰²,
李春国³,
谢威¹

1.
陆军工程大学通信工程学院南京 210007
2.
火箭军工程大学通信工程学院西安 710025
3.
东南大学信息科学与工程学院南京 210096

基金项目: 国家自然科学基金(62471488, 62471486, 62271503, 62071485)，江苏省自然科学基金(BK20231485)

详细信息

作者简介:
周涛：男，博士生，研究方向为通感一体、可重构超表面

许魁：男，教授，研究方向为无线通信、通信信号处理

夏晓晨：男，副教授，研究方向为无线通信、通信信号处理

胡国杰：男，博士，讲师，研究方向为无线通信、可重构超表面

李春国：男，教授，研究方向为无线通信、通信信号处理

谢威：男，副教授，研究方向为无线通信、通信信号处理

通讯作者:
许魁　lgdxxukui@sina.com

中图分类号: TN929.5
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- 被引次数: 0
出版历程
- 收稿日期: 2024-07-15
- 修回日期: 2024-11-26
- 网络出版日期: 2024-11-29

Movable-Element Simultaneously Transmitting And Reflecting Reconfigurable Intelligent Surface-Assisted Integrated Sensing And Covert Communication System: Joint Active and Flexible Passive Beamforming Design

1.
College of Communication Engineering, Army Engineering University of PLA, Nanjing, 210007, China
2.
College of Communication Engineering, Rocket Force University of Engineering, Xi’an, 710025, China
3.
School of Information Science and Engineering, Southeast University, Nanjing, 210096, China

Funds: The National Natural Science Foundation of China (62471488, 62471486, 62271503, 62071485), The Natural Science Foundation of Jiangsu Province of China (BK20231485)

摘要

摘要: 由于通信与目标感知波形的耦合共用，通感一体(ISAC)系统更容易面临信息泄露的风险。该文从隐蔽通信角度，研究了具有可移动阵元的同时透射和反射智能超表面(ME-STAR-RIS)辅助的ISAC系统。首先引入了ME-STAR-RIS，其阵元可在一定范围内移动，以获取更有利的信道条件。根据离散阵元部署位置模型，构建了ME-STAR-RIS辅助ISAC系统的波束优化模型，旨在联合设计ISAC基站(BS)处的主动波束成形以及ME-STAR-RIS处的柔性被动波束成形(包括阵元位置、相移和振幅系数)，在隐蔽通信质量约束下，最大化感知目标的探测波束增益。进而提出一种双层迭代优化算法有效求解主动和柔性被动波束成形。仿真结果验证了所提算法的有效性，并表明阵元移动能够有利于提升ISAC系统性能。
- 通信感知一体化 /
- 隐蔽通信 /
- 同时透射和反射智能超表面 /
- 可移动阵元
Abstract: Due to the sharing of communication and sensing waveforms, Integrated Sensing And Communication (ISAC) systems are more vulnerable to the risk of information leakage. The Movable Element Simultaneously Transmitting And Reflecting Reconfigurable Intelligent Surface (ME-STAR-RIS) assisted ISAC system from the perspective of covert communication is investigated in this paper. The ME-STAR-RIS array elements can be moved within a certain range to obtain more favorable channel conditions. Based on the discrete element position model, the joint beamforming optimization problem is formulated which aims to jointly design the active beamforming at the ISAC Base Station (BS) and the flexible passive beamforming (including array element positions, phase shifts, and amplitude coefficients) at the ME-STAR-RIS to maximize the probing beam gain at the sensing target within covert communication quality constraints. A two-layer iterative algorithm is proposed to efficiently solve the active and flexible passive beamforming problem. The simulation results verify the effectiveness of the proposed algorithm and show that by moving the elements, a narrower and stronger detection beam can be obtained, which is conducive to improving the system’s performance.

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图 1 ME-STAR-RIS辅助的ISCC系统

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图 2 仿真场景

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图 3 不同传输功率下的性能对比及算法目标函数收敛性

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图 4 相移差及阵元位置收敛性分析

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图 5 波束方向图性能分析

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1 基于惩罚的双层迭代算法

(1) 初始化$\left\{ {{{\boldsymbol{W}}}_l^{\left( 0 \right)},{{{\boldsymbol{S}}}^{\left( 0 \right)}}} \right\}$, $ {\text{\{}}{\hat {\boldsymbol{q}}}_u^{(0)}{\text{\} }} $和$ {\text{\{}}{{\boldsymbol{q}}}_u^{(0)}{\text{\} }} $，外层迭代计数　$t = 0$，最大迭代次数$t_{{\text{max}}}^{{\text{in}}}$和$t_{{\text{max}}}^{{\text{out}}}$，收敛精度 $\mu $，惩罚系数$ \eta $和　$ {\eta _{\min }} $, $ \rho $和$ {\rho _{\max }} $。更新系数$\omega < 1$。
(2) Outer Loop：重复(3)～(10)
(3) 　求解$ {\widetilde \wp _{1.1}} $获取$\left\{ {{{{\boldsymbol{W}}}_l},{{\boldsymbol{S}}}} \right\}$，目标函数值${f_t}$，特征分解获取${{\boldsymbol{w}}}_l^t$。
(4) 　初始化内层循环参数。
(5) 　　Inner Loop：重复(6)～(8)
(6) 　　　迭代求解$ {\widetilde \wp _{1.{\text{2}}}} $获取$ {\text{\{}}{{{\boldsymbol{q}}}_u}{\text{\} }} $。
(7) 　　　根据式(22)和式(24)更新$ {\text{\{}}{\hat {\boldsymbol{q}}}_u^t{\text{\} }} $。
(8) 　　　更新惩罚因子 $ \rho {\text{ = min}}\left( {{\text{2}}\rho ,{\rho _{\max }}} \right) $。
(9) 　　　Until达到内层收敛精度或达到最大迭代次数$t_{{\text{max}}}^{{\text{in}}}$，输　　　　　出$ {\text{\{}}{{\boldsymbol{q}}}_u^t{\text{\} }} $。
(10) 　令$ \eta = \min \left( {\omega \eta ,{\eta _{\min }}} \right) $, $t = t + 1$。
(11) Until 外层目标函数收敛或达到最大迭代次数$t_{{\text{max}}}^{{\text{out}}}$。
(12) End
(13) 输出：$\left\{ {{{\boldsymbol{w}}}_l^,{{{\boldsymbol{S}}}^},{{\boldsymbol{q}}}_u^*} \right\}$。

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表 1 仿真参数

参数名称	数值	参数名称	数值	参数名称	数值	参数名称	数值
目标角度(°)	±50	BS天线数	6	隐蔽系数	0.1	内惩罚因子$\rho $	0.001
目标距离(m)	20	可移动阵元数	15	外惩罚因子	1 000	${\rho _{\max }}$	10
莱斯因子(dB)	5	阵元位置数	30	$ {\eta _{\min }} $	10^–4	最大迭代次数	30
噪声功率(dBm)	–110	数据块长度	1 000	缩放系数$ \omega $	0.7	收敛精度	0.001

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