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 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.
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.
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.
Covert communication enforces the transmitted signal to be indistinguishable from other signals under wireless environment, making it difficult for an eavesdropper to detect and intercept the message. The most common approach within covert systems is the augmentation of artificial noise (AN), ensuring reliable transmission. However, this strategy becomes problematic when the eavesdropper's position is uncertain, as continuous amplification of interference power can precipitate a substantial decline in covert communication capacity. In this paper, we investigate the covert communication between legitimate transmitter (i.e., Alice) and full duplex receiver (i.e., Bob) in the presence of the location uncertainties of the eavesdropper (i.e., Willie). We first derive the sufficient condition for achieving covert communication through robustness analysis. Then, we derive the effective throughput to measure the covert communication capacity. Afterward, by using joint optimization technology, the optimal AN power of Bob and the number of antennas for Alice are jointly designed to maximize the effective throughput subject to a covertness constraint. Theoretical analysis indicates that reducing the AN power while increasing the number of antennas helps to improve the system capacity, the effective throughput between Alice and Bob is inversely proportional to the distance between them. Finally, the validity of our analytical approach is corroborated by simulation results.
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.
Covert transmission is investigated for a cooperative deception strategy, where a cooperative jammer (Jammer) tries to attract a multi-antenna adversary (Willie) and degrade the adversary’s reception ability for the signal from a transmitter (Alice). For this strategy, we formulate an optimization problem to maximize the covert rate when three different types of channel state information (CSI) are available. The total power is optimally allocated between Alice and Jammer subject to the Kullback-Leibler (KL) divergence constraint, which can be expressed analytically and be widely used as a covertness measurement. Different from the existing literature, in our proposed strategy, we also determine the optimal transmission power at the jammer when Alice is silent, while existing works always assume that the jammer’s power is fixed. Specifically, we apply the S-procedure to convert infinite constraints into linear-matrix-inequalities (LMI) constraints. When statistical CSI at Willie is available, we convert double integration to single integration using asymptotic approximation and substitution method. Finally, our simulation results show that for the proposed strategy, the covert rate is increased with the number of antennas at Willie. Moreover, compared to the benchmark, our proposed strategy is more robust in the presence of imperfect CSI.
The channel state information (CSI) of malicious users in the field of physical layer security is usually difficult to obtain due to the users’ passive listening. However, as sensing is integrating into the cellular network, it becomes feasible to acquire the CSI of passive eavesdroppers. Motivated by this, we propose a novel sensing-aided secure communication (SASC) scheme in this paper, which is implemented by a two-stage transmission protocol including beam sensing of the eavesdropper’s CSI and secure communication to the legitimate user against the eavesdropper. In the first stage, the base station (BS) needs to decide the number of sensing beamsL, and we derive the closed-form Cramer-Rao bound (CRB) to establish the relationship between the estimated angle range for the eavesdropper’s location andL, where a largerLfor beam sensing returns a tighter CRB to locate the eavesdropper. In the second stage, the BS designs the beamforming vector to transmit confidential data to the legitimate user and avoid leakage to the eavesdropper in the estimated range. As sensing affects the subsequent secure communication, we decouple the non-convex two-stage joint optimization problem into two subproblems and solve it by backward induction. In particular, in the secrecy beamforming subproblem givenL, we investigate the worst-case information leakage by constructing a convex hull to approximate the angle range from sensing. Then we develop a semi-closed-form solution of robust secrecy beamforming vector, and use it for the other subproblem to decide initialL. To achieve this goal, we also obtain a semi-closed-form solution ofLby considering all potential estimated results in the worst case. Finally, we present simulation results to show the effectiveness and robustness of the proposed SASC scheme as compared to various benchmarks.