Empowered by the integrated sensing and communication capability, this paper proposes a new two-stage artificial noise (AN)-assisted secure beamforming design towards physical layer security enhancement. Specifically, in the first stage a nearly omni-directional AN is used for sensing the eavesdropper, where the AN is radiated istropically except in the direction of the communication user. With the known channel knowledge of the eavesdropper, a spatially AN is transmitted in the second stage to deliberately degrade the eavesdropper. To balance the sensing and secure communication performance, we aim to maximize the effective secrecy rate by jointly optimize the time allocation and the transmit beamforming in both stages. A efficient optimization algorithm based on weighted minimum mean square error is then developed to solve the formulated non-convex problem. Simulation results are provided to demonstrate the performance advantage of our proposed design over the existing benchmark schemes in terms of achieving a larger effective secrecy rate.
Empowered by the integrated sensing and communication capability, this paper proposes a new two-stage artificial noise (AN)-assisted secure beamforming design towards physical layer security enhancement. Specifically, in the first stage a nearly omni-directional AN is used for sensing the eavesdropper, where the AN is radiated istropically except in the direction of the communication user. With the known channel knowledge of the eavesdropper, a spatially AN is transmitted in the second stage to deliberately degrade the eavesdropper. To balance the sensing and secure communication performance, we aim to maximize the effective secrecy rate by jointly optimize the time allocation and the transmit beamforming in both stages. A efficient optimization algorithm based on weighted minimum mean square error is then developed to solve the formulated non-convex problem. Simulation results are provided to demonstrate the performance advantage of our proposed design over the existing benchmark schemes in terms of achieving a larger effective secrecy rate.
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.
In this paper, we consider the joint beamforming design in secure integrated sensing and communication (ISAC) systems, where the active eavesdropper intercepts the transmitted confidential information with an external passive eavesdropper. To improve the sensing performance while preventing the potential eavesdropping, the base station transmits a signal consisting of information symbols and sensing waveform, in which the sensing waveform is also used as artificial noise to interfere with eavesdroppers. Under this setup, we formulate the communication and sensing beamforming design problem, which aims to enhance the transmit beampattern performance, while ensuring the quality of service (QoS) of communication transmission and the secure communication constraint. Furthermore, we propose the semi-definite relaxation (SDR) algorithm to solve the non-convex problem. Numerical results demonstrate the effectiveness of the proposed scheme in both sensing and secure communication.
This paper develops a two-phase secure integrated sensing and communication (ISAC) framework, where a dual-functional transmitter (Alice) detects the existence of a potential eavesdropper (Eve) as a sensing target in the first phase. In the second phase, Alice adapts her secure transmission strategy based on the sensing outcome of the first phase. A distinct aspect of our proposed two-phase framework is the derivation of the overall effective secrecy rate across both phases. This is achieved by seamlessly incorporating the a priori probability of Eve’s presence, the sensing false alarm rate, and the sensing detection probability directly into the effective secrecy rate as weighting coefficients. For system design, we aim to maximize the overall effective secrecy rate subject to Alice’s average transmit power remaining below a predetermined threshold. To address the resulting non-convex design problem, an algorithm based on semi-definite relaxation (SDR) and double-layer optimization is proposed. Our numerical results show that the proposed two-phase secure ISAC framework significantly enhances the secrecy rate compared to a conventional physical layer security (PLS) system if Eve is present with a low probability.
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 addresses physical layer security in unmanned aerial vehicle (UAV)-assisted communication. We propose a secure beamforming optimization algorithm based on an Improved Artificial Bee Colony (I-ABC) framework to solve the non-convex problem of maximizing the system’s secrecy rate. The algorithm concurrently designs the information-bearing signal beam and the artificial noise (AN) beam, ensuring quality of service (QoS) for the legitimate user while degrading the eavesdropper’s channel. A key innovation is the I-ABC’s channelaware dynamic perturbation strategy, which effectively explores the non-convex solution space to avoid local optima and ensure rapid convergence. Simulation results demonstrate that our algorithm exhibits rapid convergence and significantly enhances the secrecy rate compared to schemes without AN, confirming its efficacy for secure transmission.
Exploiting the randomness embedded in wireless channels, the physical-layer security techniques can provide additional security robustness against malicious eavesdropping at the physical layer of communication systems. To further this line of study, this thesis focuses on developing advanced multi-antenna transmission strategies for enhancing the secrecy performance of wireless communication systems. Assuming perfect channel feedback from the desired receiver and none from the eavesdropper, we consider beamforming with smartly injected artificial noise, aiming to confuse the eavesdropper whilst leaving the desired receiver unaffected. The system parameters are either chosen to be fixed for all transmissions, or adaptively adjusted based on the channel feedback from the desired receiver. For both cases, we provide novel and explicit design solutions for achieving the maximum throughput subject to a secrecy outage constraint. We then derive accurate approximations for the maximum throughput, and give new insights into the additional power cost for achieving a higher security level and the throughput gain of adaptive transmission over non-adaptive transmission. Having investigated the perfect feedback scenario, we then relax the feedback assumption and consider practical effects imposed by limited feedback constraints on the channel from the desired receiver to the transmitter. To deal with quantization error due to limited feedback whilst also accounting for unknown channel of the eavesdropper, we specify a connection outage constraint to guarantee the reliability of desired communication and a secrecy outage constraint to guard against malicious eavesdropping. Under dual outage constraints, we derive a novel optimized rate-adaptive transmission design to maximize the average secrecy throughput. New insights regarding the optimal power/feedback allocation and the number of feedback bits required for efficient quantization are obtained through our analysis. Our preceding study focused on isolated point-to-point transmission without any interference. However, the performance of contemporary wireless networks is often limited by interference from concurrent transmissions. To characterize the impact of interference on secure communication, we consider an interference-limited large-scale network. To confuse the malicious eavesdroppers, in addition to information-bearing signals, the transmitters are designed to generate artificial noise through either beamforming or antenna sectoring in a distributed manner. For both cases, using tools from stochastic geometry, we provide a statistical characterization of the reliability performance of desired communication and the secrecy performance against eavesdropping. We then investigate the networkwide secrecy throughput performance and optimize the transmit power allocation. Our analysis reveals interesting differences between the beamforming and sectoring approaches in terms of the optimal power allocation and the maximum networkwide secrecy throughput.