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International Conference on Communications

Secure Transmission for MISO Integrated Sensing and Communication Secrecy Systems

Yajie Zhang, Zengbao Zhu, Qimei Cui, Guoshun Nan, Xuefei Zhang

Published Jun 9, 2024• 6 citations
Publisher

Abstract

Integrated Sensing and Communication (ISAC) can reuse the same spectrum and hardware resources for communication and radar sensing, which is a promising technology to alleviate spectrum congestion. Recently, there has been an increasing research interest in the physical layer secrecy aspects of ISAC systems. This paper studies a basic multiple-input single-output ISAC secrecy system, where a multi-antenna base station transmits a unified signal to sense a point target and communicate to a single-antenna receiver in the presence of$K$single antenna eavesdroppers. Under this setup, a sensing signal-to-noise ratio (SNR) constrained secrecy rate maximization problem has been formulated. We showed that the problem can be reformulated as a convex semidefinite programming problem and proved that beamforming is the optimal transmission scheme. We derived two low-complexity semiclosed-form optimal beamforming solutions and one suboptimal closed-form solution. Numerical results demonstrate that the proposed solutions attain the optimum of the sensing SNR constrained secrecy rate maximization problem and have lower computational complexity than the existing method.

DOI
10.1109/icc51166.2024.10622171

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Integrated Sensing and Communication (ISAC) can reuse the same spectrum and hardware resources for communication and radar sensing, which is a promising technology to alleviate spectrum congestion. Recently, there has been an increasing research interest in the physical layer secrecy aspects of ISAC systems. This paper studies a basic multiple-input single-output ISAC secrecy system, where a multi-antenna base station transmits a unified signal to sense a point target and communicate to a single-antenna receiver in the presence ofKKKsingle antenna eavesdroppers. Under this setup, a sensing signal-to-noise ratio (SNR) constrained secrecy rate maximization problem has been formulated. We showed that the problem can be reformulated as a convex semidefinite programming problem and proved that beamforming is the optimal transmission scheme. We derived two low-complexity semiclosed-form optimal beamforming solutions and one suboptimal closed-form solution. Numerical results demonstrate that the proposed solutions attain the optimum of the sensing SNR constrained secrecy rate maximization problem and have lower computational complexity than the existing method.
The advances of multi-antenna techniques has recently led to renewed interest in physical-layer secrecy, a meaningful topic that enables us to prevent eavesdroppers from retrieving information intended for a legitimate user through physical layer designs. This paper address a secrecy-rate maximization problem for the scenario of a multi-input single-output channel listened by multiple multi-antenna eavesdroppers; e.g., in downlink. This problem is nonconvex and has no analytical solution. Through a careful analysis and reformulation, we show that the secrecy-rate maximization problem has a convex equivalent in form of a semidefinite program (SDP). We also prove that the respective optimal transmit covariance generally can yield a rank-one structure, implying that transmit beamforming is secrecy-rate optimal in the considered scenario. Simulation results are also provided to illustrate that the optimal transmit design solved by our SDP approach can yield significantly improved secrecy rates than an existing closed-form design.
This paper considers secure transmission design for multiple-input-single-output multiple multi-antenna eavesdroppers networks with finite alphabet inputs. To improve the achievable secrecy rate, the joint optimization of beamforming vector and transmitting power is studied. We transform the multivariable problem into a single-variable problem, and then derive the beamforming vector and the transmitting power using one-dimensional search method. Specially, the secure transmission designs in the extremely signal-to-noise ratio (SNR) regime are investigated. In the low SNR regime, the problem of beamforming design is transformed into a semi-definite programming problem, which can be handled by interior-pointbased methods, and the optimal transmitting power is obtained. Besides, two different secure schemes, which are zero-force beamforming scheme and joint beamforming and jamming scheme, are proposed to increase the achievable secrecy rate at high SNR. Numerical results demonstrate that the proposed schemes significantly improve the secrecy performance of the system.
This paper studies the joint secure transceiver design for the full-duplex integrated sensing and communication (ISAC) system, in which the base station performs the target tracking and communicates with the downlink and the uplink users by reusing the resources. Here, the target, referred to as Eve, is a potential eavesdropper with the intention of intercepting both the downlink and the uplink information. The security problem of the full-duplex ISAC system has not been studied well, where the sensing and communication signals suffer from the serious interference. In this paper, we jointly design the information beamformer, the radar waveform, the uplink communication receive filter, and the radar receive filter to achieve the downlink and uplink communication security and the target tracking. Specifically, both the Eve’s signal-to-interference-plus-noise ratio minimization and the secrecy rate maximization problems, subject to the sensing and the communication constraints, are formulated for the ISAC system from the perspectives of the quality of service and the secrecy rate. An iterative algorithm is proposed for solving the formulated problems. We prove that, under appropriate conditions, the proposed iterative algorithm converges to the Karush-Kuhn-Tucker optimal point of the original problem without the rank 1 constraint. We further extend the joint design to the case of the imperfect wiretap channel and the angle uncertainty. Numerical results show that our scheme remarkably outperforms the benchmark approaches. The performance is close to that of designing the secure communication and the sensing separately.
This paper studies the secrecy capacity of the multiple input single output (MISO) secrecy channel where a transmitter is communicating to a receiver in the presence of K eavesdroppers. The transmitter is equipped with multiple antennas, while the receiver and all the eavesdroppers each has a single antenna. The transmitter maximizes the communication rate, while concealing the message from all the eavesdroppers. It is known that the maximum achievable secrecy rate is obtained with the optimal transmit covariance matrix that maximizes the minimum difference between the mutual information of the secrecy user channel and those of the eavesdroppers channels. The maximum secrecy rate computation can thus be formulated as a non-convex max-min problem, which cannot be solved efficiently. This paper proposes an efficient algorithm based on quasi-convex programming, which not only leads to the optimal transmit covariance matrix, but also guarantees that it is always rank-one at any search step with finite accuracy. Such a guaranteed rank-one covariance matrix is critical to practical implementations of MISO secrecy transmission beam-forming.
The notion of providing secure communication via physical-layer designs has gained much attention in recent studies. This paper considers the transmit covariance design for a generalized secrecy rate maximization (SRM) problem under the scenario of a multi-input single-output channel overheard by multiple multi-antenna eavesdroppers. This generalized SRM design encompasses various existing SRM designs, e.g., the per-antenna power constrained design and the interference temperature constrained design. While the considered generalized SRM problem is nonconvex by nature, this paper shows that the problem can actually be solved in a convex fashion, by recasting the generalized SRM problem as a semidefinite program (SDP). The development of the solution to the generalized SRM shows that transmit beamforming is generally an optimal transmit strategy. Simulation results are also provided to demonstrate the secrecy-rate performance gains of the proposed algorithm over some closed-form, but suboptimal algorithms.
In recent years there has been growing interest in study of multi-antenna transmit designs for providing secure communication over the physical layer. This paper considers the scenario of an intended multi-input single-output channel overheard by multiple multi-antenna eavesdroppers. Specifically, we address the transmit covariance optimization for secrecy-rate maximization (SRM) of that scenario. The challenge of this problem is that it is a nonconvex optimization problem. This paper shows that the SRM problem can actually be solved in a convex and tractable fashion, by recasting the SRM problem as a semidefinite program (SDP). The SRM problem we solve is under the premise of perfect channel state information (CSI). This paper also deals with the imperfect CSI case. We consider a worst-case robust SRM formulation under spherical CSI uncertainties, and we develop an optimal solution to it, again via SDP. Moreover, our analysis reveals that transmit beamforming is generally the optimal transmit strategy for SRM of the considered scenario, for both the perfect and imperfect CSI cases. Simulation results are provided to illustrate the secrecy-rate performance gains of the proposed SDP solutions compared to some suboptimal transmit designs.