This paper proposes a near-field integrated sensing and covert communication (ISCC) system, where Alice transmits covertly to Bob against Willie’s detection. We jointly optimize hybrid digital and analog beamforming and radar waveforms via the weighted minimum mean square error and manifold optimization algorithm to maximize covert rate while ensuring security, and use the extended Kalman filter to track the adversarial target in real-time for adaptive parameter adjustment. By addressing covertness constraints including leakage power, the proposed system ensures a low probability of detection while enabling superior system performance. The simulation results demonstrate that the proposed method provides secure communication and reliable target tracking under various conditions, achieving effective communication with Bob even in the presence of detection threats. The results validate the effectiveness of the proposed ISCC system in near-field scenario.
This paper proposes a near-field integrated sensing and covert communication (ISCC) system, where Alice transmits covertly to Bob against Willie’s detection. We jointly optimize hybrid digital and analog beamforming and radar waveforms via the weighted minimum mean square error and manifold optimization algorithm to maximize covert rate while ensuring security, and use the extended Kalman filter to track the adversarial target in real-time for adaptive parameter adjustment. By addressing covertness constraints including leakage power, the proposed system ensures a low probability of detection while enabling superior system performance. The simulation results demonstrate that the proposed method provides secure communication and reliable target tracking under various conditions, achieving effective communication with Bob even in the presence of detection threats. The results validate the effectiveness of the proposed ISCC system in near-field scenario.
Emerging wireless applications pursue a paradigm shift towards the integrated system that is capable of secure data transmission and high-resolution sensing in near-field environments. Conventional far-field use-cases suffer from the fundamental limitations in security, spatial precision, and spectral coexistence. Against this backdrop, this paper investigates an integrated covert communications and sensing (ICCS) system operating in the near-field environment. Specifically, the transmitter (Alice) aims to covertly convey messages to legitimate receivers (Bobs), while circumventing the detection by the eavesdropper (Willie) as well as improving the sensing performance at the target. To elevate communication performance, we aim to maximize the achievable sum rate to jointly optimize the communication and sensing beamforming matrices at Alice. The optimization problem is subject to multiple constraints with coupled variables: the transmit power budget at Alice, the minimum communication rate requirements for Bob, the Crameˊr-Rao bound (CRB) constraint to ensure accurate parameter estimation in sensing, and the covertness constraint against Willie’s detection. Given the non-convex nature of the formulated problem, an efficient successive convex approximation and semidefinite relaxation algorithms are proposed. In addition, we provide a theoretical analysis to confirm the convergence behaviour of the proposed algorithm, which can achieve the near-optimal solution. Finally, the numerical results are presented to highlight the superiority of the proposed ICCS system over existing counterparts. These results numerically verify the effectiveness of the proposed approach in enhancing communication rates while maintaining sensing performance and covertness in the near-field regime.
In this letter, we propose a near-field secure integrated sensing and communication (ISAC) system architecture, where the ISAC system simultaneously performs target detection and tracking while transmitting communication information to downlink users. However, in the presence of malicious eavesdropping devices, the security of communication transmission in ISAC systems cannot be guaranteed. Near-field effects introduce an additional advantage in the distance dimension, which improves the accuracy of target distance and angle estimation. Simultaneously, beamforming can be spatially focused at specific points to prevent information leakage. Motivated by these benefits, We construct a weighted optimization framework aimed at jointly maximizing the overall secrecy rate and reducing the Cramér-Rao Bound (CRB) for target estimation in near-field scenarios, while adhering to communication demands and total power limitations of the system. By integrating fractional programming (FP) and semidefinite relaxation (SDR) techniques, we jointly optimize the transmit waveform covariance matrix and the beamforming vectors to enhance both sensing accuracy and secure transmission performance simultaneously. Numerical results reveal that the secure near-field ISAC scheme can effectively achieve a synergy enhancement between sensing and secure communication while maintaining reliable system performance.
This paper investigates the covert communication in the scenario of counter detection. In traditional covert communication design where the uncertainty of the position of the Warden Willie typically reduces covert performance. To overcome this limitation, we leverage the sensing ability of the ISAC system in a new way to reduce the channel uncertainty between Alice and Willie, thereby enabling less conservative power allocation and significantly improving the achievable covert throughput. In the first stage, the dual functional sensing and communication (DFRC) base station Bob sends joint signals to estimate the azimuth of Willie and transmits information to Alice at the same time. In the second stage, Alice uses the obtained azimuth information of Willie to adjust transmit power while meeting the covert constraints. We build a mathematical model of azimuth angle estimation error and connect it with the Cramér-Rao Bound (CRB) to change it into distance error. This connects sensing accuracy with channel state information (CSI) uncertainty in a linear way, allowing Alice to adopt a higher transmit power while still satisfying the covert constraint, and thus improving the achievable covert throughput. To increase the covert throughput of the user, we use a layered solving strategy to decouple the original problem. First, we use S-procedure to change the constraint on possible distance error into a linear matrix inequality (LMI) constraint and then find the upper limit of transmit power on the user side. Second, we combine it with the uplink communication link rate constraint to find the closed form expression of the resource allocation strategy in vector space. Finally, we use one dimensional search to find the optimal time slot allocation strategy. Simulation results show that the proposed two-stage protocol effectively improves the achievable covert throughput by reducing position uncertainty through sensing.
This letter investigates the robust beamforming design for an integrated sensing and covert communications system, where the transmitter (Alice) performs some sensing task and simultaneously communicates with multiple legitimate users (Bobs) covertly, evading detection by the eavesdropper (Willie). Considering the impact of imperfect channel state information (CSI) of Alice-to-Bobs and Alice-to-Willie links, we formulate a robust beamforming optimization problem to minimize the Cramér-Rao bound for sensing parameter while satisfying the total transmit power, the signal-to-interference-plus-noise ratio and covertness constraints for communication. An iterative algorithm, employing semi-definite programming and successive convex approximation, is proposed to address this challenging problem. Numerical results validate the effectiveness of the proposed scheme, highlighting the robustness of the optimized beamforming design under imperfect CSI.
In this work, we propose a two-stage integrated sensing and communication (ISAC) framework for exploiting the benefits of utilizing ISAC's detection capability in covert communications. Specifically, in the first stage a full-duplex transceiver Bob detects the presence of a warden Willie while performing uplink transmissions to another transceiver Alice. Then, in the second stage Bob helps Alice's covert downlink transmission via jamming as per his detection outcome in the first stage. We optimally design the covert ISAC system to maximize the formulated overall covert rate subject to a covertness constraint, an average power constraint at Bob, and an uplink rate requirement. As shown in our examinations, the proposed two-stage framework significantly outperforms a benchmark scheme without the detection function in terms of achieving a higher covert rate. This, for the first time, explicitly demonstrates the superiorities of using ISAC's detection function to enhance covert communications.
Covert communication conceals wireless transmission activity, but conventional multi-antenna designs rely mainly on spatial beamforming and can be constrained by limited spatial degrees of freedom. This paper investigates polarization-reconfigurable antenna (PRA)-aided multiple-input multiple-output (MIMO) covert communication, where Alice and Bob perform transmit and receive polarforming, respectively, and Willie uses a vertically polarized antenna for radiometric detection. We jointly optimize the transmit covariance matrix and the transmit and receive phase shift vectors to maximize Bob's achievable rate under the covertness and transmit power constraints. Under Gaussian signaling, perfect polarized channel state information, and known noise power at Willie, we derive his optimal radiometric threshold and exact minimum detection error probability (DEP) for a finite observation length, and convert the DEP requirement into a deterministic constraint on his received signal power. We further prove that, for a fixed transmission design, positive signal leakage becomes detectable as the observation length tends to infinity. To solve the design problem for a finite observation length, we develop an alternating optimization (AO) algorithm with a generalized water-filling covariance update and closed-form phase updates. Numerical results validate the exact DEP analysis and the rapid convergence of the proposed algorithm. Compared with the sufficient divergence-based condition, the exact covertness constraint permits a 0.99--1.12~dB higher received signal-to-noise ratio (SNR) at Willie, while joint transmit and receive polarforming provides a rate gain of up to 53.8% over the considered benchmark schemes.