Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Integrated Sensing and Covert Communication

ZHOU Xiaobo; RUAN Danyang; ZHOU Xiuying; XIA Guiyang; SHU Feng

doi:10.11999/JEIT240643

Volume 47 Issue 2

Feb. 2025

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Article Navigation > Journal of Electronics & Information Technology > 2025 > 47(2): 375-385

ZHOU Xiaobo, RUAN Danyang, ZHOU Xiuying, XIA Guiyang, SHU Feng. Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Integrated Sensing and Covert Communication[J]. Journal of Electronics & Information Technology, 2025, 47(2): 375-385. doi: 10.11999/JEIT240643

Citation:

ZHOU Xiaobo, RUAN Danyang, ZHOU Xiuying, XIA Guiyang, SHU Feng. Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Integrated Sensing and Covert Communication[J]. Journal of Electronics & Information Technology, 2025, 47(2): 375-385. doi: 10.11999/JEIT240643

Citation:

ZHOU Xiaobo, RUAN Danyang, ZHOU Xiuying, XIA Guiyang, SHU Feng. Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Integrated Sensing and Covert Communication[J]. Journal of Electronics & Information Technology, 2025, 47(2): 375-385. doi: 10.11999/JEIT240643

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Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Integrated Sensing and Covert Communication

doi: 10.11999/JEIT240643 cstr: 32379.14.JEIT240643

1.
School of Information and Artificial Intelligence, Anhui Agricultural University, Hefei 230036, China
2.
School of Information and Communication Engineering, Hainan University, Haikou 570228, China

Funds: The National Natural Science Foundation of China (62371004, 62301005), The University Synergy Innovation Program of Anhui Province (GXXT-2022-055)

Received Date: 2024-07-23
Rev Recd Date: 2024-12-26

Available Online: 2025-01-06

Publish Date: 2025-02-28

Abstract

Abstract

Objective Integrated Sensing and Communication (ISAC) systems are considered key technologies for the upcoming 6G networks, offering a unified platform for wireless communication and environmental sensing. To enhance the security of ISAC systems, an Integrated Sensing and Covert Communication (ISACC) system is proposed. Additionally, an Intelligent Reflecting Surface (IRS)-assisted ISACC scheme is proposed to address the limitation of existing ISACC research, which cannot be applied to scenarios without a Line-of-Sight (LoS) link between the Base Station (BS) and the target. In this context, the average Cramér-Rao Lower Bound (CRLB) is adopted as a metric for sensing performance, aiming to overcome the limitations of traditional beampatterns in quantifying sensing performance directly. Methods The detection performance at warden Willie is first analyzed. An analytical expression for the average CRLB is then derived. Based on this, an optimization problem is formulated to minimize the average CRLB, subject to communication rate, covertness, and IRS phase shift constraints. The optimization problem is challenging to solve directly due to the coupling of the sensing covariance matrix, communication beamforming, and IRS reflective beamforming in the objective function, communication rate constraint, and covertness constraint. To tackle this, the optimization problem is decomposed into two subproblems: one for the sensing covariance matrix and communication beamforming optimization, and another for the IRS reflection beamforming optimization. An Alternating Optimization-based Penalty Successive Convex Approximation (AO-PSCA) algorithm is proposed to solve the two subproblems iteratively. Results and Discussions The relationship between the average CRLB, the number of IRS reflection elements, and the number of BS antennas is presented (Fig. 2). As observed, the average CRLB obtained by the AO-PSCA algorithm and the IRS random phase algorithm decreases as the number of IRS elements increases. This is because a larger number of IRS elements not only enhances covert communication performance but also improves the quality of the virtual link between the BS and the sensing target. Additionally, the proposed AO-PSCA algorithm outperforms the IRS random phase scheme, highlighting the importance of designing IRS reflection coefficients. Furthermore, as the number of BS antennas increases, the average CRLB decreases, since more antennas simultaneously improve both target sensing and covert communication performance. The relationship between the average CRLB, covertness threshold, and communication rate threshold is shown (Fig. 3). It can be seen that the average CRLB decreases as the covertness parameter $\varepsilon $ increases. This indicates that increasing the covertness parameter improves the sensing performance of the ISACC system. The reason is that a larger covertness value of $\varepsilon $ makes it easier to satisfy the covertness constraints, thereby allowing more resources for communication and sensing. In contrast, the average CRLB increases with the communication rate requirement, as a larger value of $ \varGamma $ requires more system resources, leaving fewer resources for radar sensing. The relationships between the average CRLB, average maximum transmit power, and symbol length, as well as between average maximum transmit power, communication signal power, and sensing signal power, are presented (Fig. 4). It can be observed that the average CRLB decreases as the average maximum transmit power increases. This is due to the increase in both sensing and communication signal powers with higher transmit power. The average CRLB also decreases as the symbol length increases, as a larger symbol length improves target sensing performance. The relationship between the beampattern, angle, and average maximum transmit power is illustrated (Fig. 5). The beampatterns are focused on their main lobe, with the sensing target located at 0°. Due to communication rate and covertness constraints, random fluctuations appear in the side lobe regions of the beampatterns. Moreover, the beampattern values increase with the average maximum transmit power, indicating that increasing transmit power effectively enhances both target sensing and covert communication performance. Conclusions The IRS-assisted ISACC system is investigated in this work. An optimization problem is formulated to minimize the average CRLB, subject to constraints on covertness, maximum transmit power, communication rate, and IRS phase shifts. The AO-PSCA algorithm is proposed for the joint design of the sensing covariance matrix, communication beamforming, and IRS phase shifts. Simulation results demonstrate that the proposed ISACC scheme, assisted by IRS, can effectively balance target sensing and covert wireless communication performance.
- Integrated Sensing and Communication (ISAC),
- Intelligent Reflecting Surface (IRS),
- Covert communication,
- Cramér-Rao Lower Bound (CRLB),
- Beamforming

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References(17)

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