The open and vulnerable nature of wireless channels exacerbates security risks in integrated sensing and communication (ISAC) systems, especially when the sensing targets act as potential eavesdroppers (Eves), and these risks intensify with collusion among Eves. To address this challenge, this paper investigates a novel strategy for a robust reconfigurable intelligent surfaces (RIS)-assisted secure ISAC system, where an ISAC base station facilitates simultaneous secure communication with legitimate users and sensing of multiple targets that may serve as Eves. We examine two different interaction mechanisms among Eves, namely, non-colluding Eves (NCE) and colluding Eves (CE), under both perfect and imperfect channel state information (CSI) assumptions. For both mechanisms, we formulate the optimization problem of maximizing users’ sum secrecy rate by jointly designing the transmit beamforming and RIS phase-shifts. This optimization is subject to constraints on transmit power, sensing requirements, and unit-modulus RIS phase shifts. The resulting non-convex problems are solved via alternating optimization (AO) algorithms. Specifically, in order to handle the severely non-convex and coupled objective function and multi-link accumulated channel error constraints caused by CE as well as imperfect CSI, we employ the majorizationminimization algorithm and the S-procedure to convert these problems into tractable forms. Simulation results validate the effectiveness of our proposed algorithms. We highlight that, at the expense of a 15% reduction in the users’ sum rate, our proposed algorithm achieves up to a 185% increase in the sum secrecy rate. Furthermore, we quantify the sensing-security trade-off by analyzing the reduction of the sum secrecy rate induced by sensing requirements, and we reveal the impacts of various factors on the sum secrecy rate, such as RIS element number, channel estimation errors, and sensing thresholds.

This letter studies proactive eavesdropping with one legitimate monitor (E) in the classical single-hop suspicious communication. Specifically, unlike all previous works that ignored the suspicious channel training phase and just considered the jamming power optimization of E in the suspicious data transmission phase to facilitate eavesdropping, this letter advances the research by comprehensively investigating the jamming power allocation of E in both phases, with the purpose of maximizing its eavesdropping success probability. Under this setup, we first derive an exact expression of the objective and reveal the existence of a fundamental trade-off in deciding the jamming power allocation, for which a simple one-dimensional search is employed to find the optimal solution. To simplify the analysis, we further derive a tight approximation of the objective and then develop a very fast alternating optimization algorithm to find the sub-optimal jamming power allocation. Moreover, we extend our analysis to the case where the channel state information is available at the suspicious transmitter via channel feedback. Simulation results demonstrate the effectiveness of our proposed scheme compared to competitive benchmarks.

We investigate the worst-case robust beamforming for simultaneous wireless information and power transfer in a multiuser beamspace massive multiple-input multiple-output (MIMO) system. The objective is to minimize the transmit power of the base station subject to the individual signal-to-interference-plus-noise ratio and the energy-harvesting constraints under imperfect channel state information. Instead of directly resorting to semi-definite relaxation, we convert the initial non-convex optimization to a power allocation problem, which greatly reduces the computational complexity. The beamforming vectors are proven to be scaled versions of the estimated channels. The optimal scaling factors are then derived in closed-form. The simulations demonstrate that the proposed robust beamforming method achieves the globally optimal point for the initial design when the channel estimation errors are small while leads to satisfactory performance when the channel estimation errors are large.

In this paper, we design robust beamforming to guarantee the physical layer security for a multiuser beam division multiple access (BDMA) massive multiple-input multiple-output (MIMO) system, when the channel estimation errors are taken into consideration. With the aid of artificial noise, the proposed design are formulated as minimizing the transmit power of the base station, while providing legal users and the eavesdropper with different signal-to-interference-plus-noise ratio. It is strictly proved that, under BDMA massive MIMO scheme, the initial non-convex optimization can be equivalently converted to a convex semi-definite programming problem and the optimal rank-one beamforming solutions can be guaranteed. In stead of directly resorting to the convex tool, we make one step further by deriving the optimal beamforming direction and the optimal beamforming power allocation in closed-form, which greatly reduces the computational complexity and makes the proposed design practical for real world applications. Simulation results are then provided to verify the efficiency of the proposed algorithm.

Wireless power transfer (WPT) is an emerging and promising technique for power supplies to mobile and portable devices. Among all approaches, magnetic resonant coupling (MRC) is an excellent one for midrange WPT, which provides high mobility, flexibility, and convenience due to its simplicity in hardware implementation and longer transmission distances. In this letter, we consider an MRC-WPT system with multiple power transmitters, one intended power receiver and multiple unintended power receivers. The optimal robust beamforming design of the complex transmit currents is investigated to achieve the minimal total source power with the worst-case mutual inductances measurement, whereas the unintended receiving powers are constrained by certain bounds. Numerical results demonstrate that the proposed algorithm can significantly improve the performance and the robustness of the MRC-WPT systems.

In this paper, we design robust downlink beamforming against the imperfect channel state information (CSI) for beam division multiple access (BDMA) massive multiple-input multiple output (MIMO) systems. Following a worst-case deterministic model, the proposed design is formulated as minimizing the power consumption of base station (BS) under different signal-to-interference-plus-noise ratio (SINR) constraints. The S-Procedure and semi-definite relaxation (SDR) are used to convert the initial non-convex optimization to a convex semi-definite programming problem. Then the optimality of SDR is strictly proved by showing the rank-one property of the optimal beamforming thanks to the orthogonal channels under BDMA scheme. More importantly, we make one step further by deriving the optimal beamforming directions and optimal beamforming power allocation of the SDR in closed-form, which greatly reduces the optimization complexity and makes the proposed design practical for a real word massive MIMO system. Simulation results are then provided to verify the efficiency of the proposed robust beamforming algorithm.

In this paper, we design robust downlink beamforming against the imperfect channel state information (CSI) for beam division multiple access (BDMA) massive multiple-input multiple output (MIMO) systems. Different from conventional approach, the optimality of semi-definite relaxation (SDR) is strictly proved by showing the rank-one property of the optimal beamforming with the orthogonal BDMA massive channels, where globally optimal robust beamforming solutions are derived. More importantly, we make one step further by deriving the optimal beamforming directions and optimal beamforming power allocation of the SDR in closed-form, which greatly reduces the optimization complexity and makes the proposed design practical for a real word massive MIMO system. Simulation results are provided to demonstrate the efficiency of the proposed algorithm.

Magnetic resonance coupling (MRC) has been utilized in wireless power transfer (WPT) to achieve mid-range contactless power supply. However, unintended users might also draw power from the transmission devices. In this letter, an MRC-WPT system with multiple power transmitters, one intended power receiver, and one unintended power receiver is investigated. We formulate a power security problem by limiting the unintended receiving power and, at the same time, maximizing the power of the intended user. Such an optimization problem is in general nonconvex. Nevertheless, a global optimal solution can be efficiently achieved with the aid of semidefinite relaxation approach. Simulation results are provided to demonstrate the effectiveness of the proposed algorithm.

In this paper, we design transmit beamforming for a full duplex base station (FD-BS) considering both self-interference mitigation and physical-layer security. The proposed design is formulated as minimizing the power consumption of FD-BS under different signal-to-interference-and-noise-ratio (SINR) constraints. Semidefinite relaxation (SDR) is used to convert the initial nonconvex optimization to be a convex semidefinite programming (SDP) problem. Then the optimality of SDR is strictly proved by showing the existence of the rank-one optimal solutions. To reduce the computational complexity, we develop zero forcing beamforming-based suboptimal algorithms, where the solutions can be obtained using golden search and closed-form solutions can be derived in each step. Simulation results are then provided to verify the efficiency of the proposed algorithms.

In this paper, we design transmit beamforming for a full-duplex base station (FD-BS) considering joint self-interference mitigation and physical-layer security enhancement. The proposed designs are formulated to minimize the power consumption of FD-BS, under different signal- to-interference-and-noise-ratio (SINR) constraints. We strictly prove the optimality of SDR by showing the existence of rank-one solutions. Simulation results are provided to demonstrate the efficiency of the proposed algorithms.

In this paper, we design joint information beam-forming and jamming beamforming to guarantee both transmit security and receive security for a full duplex base station (FD-BS). Specifically, we aim to maximize the secret transmit rate while constrain the secret receive rate to be greater than a predefined bound. We convert the original non-convex problem into a new sequence of subproblems where the semidefinite programming (SDP) relaxation can be applied to efficiently find the optimal solutions. We strictly prove that such a relaxation does not change the optimality for these subproblems. Then the global optimal solutions of the original non-convex problem can be obtained via a one-dimensional search. Simulation results are provided to verify the efficiency of the proposed algorithms.