Jul 2026· International Conference on Signal Processing and Communications· pp. 1-5· 0 citations· 14 references
Abstract
This work investigates an IRS-assisted downlink NOMA system with untrusted users under imperfect SIC, where internal eavesdropping-users intercepting each other's messages-poses distinct security challenges absent in conventional external-eavesdropper models. A key contribution is the systematic analysis of all possible decoding orders, proving that the (2,2) order yields the largest feasible power allocation region satisfying simultaneous secrecy and QoS constraints. The joint optimization of decoding order, power allocation, and IRS reflection coefficients is decomposed into two tractable subproblems: closed-form power allocation under perfect SIC and semidefinite relaxation (SDR)-based IRS phase optimization, solved via an alternating framework. Numerical results demonstrate performance improvements of 14.6% at low power (10 W) and 12.7% at high power (80 W) over benchmark schemes, validating the effectiveness of the proposed approach in balancing secrecy and service quality under practical SIC imperfections.
Physical layer security is essential for wireless communications, with artificial noise (AN) being a key technique to enhance confidentiality. However, conventional AN suffers from strict orthogonality constraints and limited design flexibility under rank-deficient channel conditions. This paper investigates power allocation for non-orthogonal artificial noise (SCO-AN), which operates in the range space of the legitimate channel, offering greater design freedom and improved secrecy. We formulate the power allocation problem between the information-bearing signal and SCO-AN under perfect channel state information (CSI), imperfect CSI, and multi-user interference. Due to the non-convex nature of the secrecy capacity function, sequential quadratic programming (SQP) is employed to obtain suboptimal power allocation solutions. Simulation results demonstrate that the proposed SQP-based scheme significantly enhances secrecy capacity compared to baseline methods, achieving up to 15% improvement in SISO systems and 20% in MIMO configurations. Computational complexity analysis confirms the efficiency of the SQP approach, requiring fewer iterations and lower per-iteration operations than alternative optimization algorithms. However, the primary contribution of this work lies in the problem formulation for SCO-AN, while the optimization method itself is a standard technique; moreover, practical factors such as channel estimation errors and hardware constraints are not fully explored, and comparisons with recent learning-based approaches as well as scalability analysis for larger MIMO systems are left for future work.
Cheng Peng, Hanqing Wang· Digital Signal and Computer...· 0 citations
Physical-layer security based on pseudo-noise (PN) superposition is a promising approach for mitigating eavesdropping in future wireless systems. However, under Shannon's capacity formulation with Gaussian signaling, achieving secrecy typically requires allocating substantial transmit power to PN, resulting in a significant reduction in achievable information rate and limiting practical applicability. This limitation is alleviated when finite-alphabet modulation schemes, such as M-ary Quadrature Amplitude Modulation ($M$-QAM), are employed, as expected in practical 6G transceivers. In this work, we analyze the information rate performance of PN-assisted systems under $M$-QAM signaling using mutual information and derive the corresponding achievable secrecy rate. The impact of PN power allocation on both the legitimate user and the eavesdropper is investigated across different modulation orders and channel conditions. Monte Carlo simulations are conducted to evaluate system behavior under varying user and eavesdropper channel conditions and to examine how PN power allocation influences secrecy performance. The results show that, at sufficiently high signal-to-noise ratio (SNR), the information rate becomes largely insensitive to PN power allocation, enabling near-perfect secrecy with $M$-QAM modulation-highlighting a key departure from Shannon-capacity-based secrecy analyses and underscoring the practicality of finite-alphabet security mechanisms for 6G wireless systems.
Fernando Moya Caceres, C. Divarathne, Yapeng Xie et al.· 0 citations
This letter investigates a pinching-antenna (PA)-assisted downlink non-orthogonal multiple access (NOMA) system with an untrusted user acting as an internal eavesdropper. By exploiting the flexibility of PAs in reconfiguring wireless channel conditions, secure information transmission for the trusted user can be achieved in the considered system. Accordingly, we formulate an optimization problem aimed at maximizing the secrecy rate by jointly optimizing the power allocation coefficients and the positions of PAs. Given that the coupling between effective channel gains and power allocation coefficients makes the problem non-convex, we employ a joint optimization algorithm to solve it effectively. Specifically, we first derive a closed-form expression for optimal power allocation, and then, an element-wise algorithm is employed to optimize the PA positions. Simulation results demonstrate that, compared with fixed antenna systems, PAs can significantly enhance the secrecy performance of NOMA systems.
We investigate secure data transmission in a unmanned aerial vehicle (UAV)-assisted Internet of Things (IoT) sensing network, focusing on maximizing multi-sensor uplink secrecy capacity under practical power constraints and severe co-channel interference. Due to the coupled signal-to-interference-plus-noise ratio (SINR) expressions and the non-smooth secrecy-rate function, the formulated power allocation problem is highly nonconvex and mathematically challenging. To efficiently solve this problem, we exploit a novel mathematical reformulation by introducing a smooth approximation of the secrecy metric and developing a computationally efficient optimization framework based on sequential quadratic programming (SQP) with analytically derived gradients. The main strength of this framework lies in its low-complexity, deterministic nature, which eliminates the need for computationally exhaustive search heuristics while guaranteeing fast, stable convergence to a Karush–Kuhn–Tucker (KKT) point. Furthermore, we incorporate a robust worst-case eavesdropper modeling approach to guarantee secure communication under severe adversarial conditions. Numerical results demonstrate that the proposed method significantly improves sum secrecy performance compared to conventional equal-power and baseline allocation schemes, proving highly scalable for real-time data collection in environmental monitoring, smart cities, and surveillance applications.
This paper investigates secure beamforming design for simultaneous proactive eavesdropping and communication in a multiuser multi-antenna system, where a full-duplex base station (FD-BS) serves multiple legitimate users, monitors a suspicious link, and suppresses multiple eavesdroppers. The proposed design is formulated as maximizing the weighted sum secrecy rate (WSSR) of legitimate users, subject to a total transmit-power requirement and a proactive eavesdropping constraint. The initial problem is hard to solve due to the high non-convexity of the objective function and the proactive eavesdropping constraint. By introducing three auxiliary variables, the original WSSR maximization problem is equivalently reformulated as a weighted minimum mean square error (WMMSE) minimization problem. The reformulated WMMSE minimization problem remains non-convex, where a block coordinate descent (BCD) algorithm based on first-order Taylor approximation is proposed to solve it iteratively. Aiming to reduce the computational complexity of the proposed method, a low complexity zero-forcing beamforming algorithm is designed. Simulation results demonstrate that the proposed algorithms can achieve superior trade-offs among communication efficiency, secrecy enhancement, and surveillance performance than conventional methods.
Chen Li, F. Zhu, Ying Zhang et al.· IEEE Open Journal of the Com...· 0 citations
This paper investigates physical-layer security in multiple-input multiple-output (MIMO) systems under imperfect channel state information (CSI). A unified framework is proposed, encompassing both cell-free and single-cell massive MIMO architectures, where CSI errors are modeled as Gaussian-distributed perturbations. The study focuses on projection-based secure precoding schemes applied to minimum mean square error (MMSE) and zero-forcing (ZF) precoders. It is shown that the resulting secure precoder can be decomposed into two components: one orthogonal to the eavesdropper’s channel subspace and another representing colored noise that characterizes the effect of CSI imperfections and constrains secrecy. Theoretical analysis demonstrates that the ZF-based projected-channel precoder preserves the ZF property under small CSI errors, thus exhibiting strong robustness. Simulation results in realistic multipath environments confirm the analysis, showing significant secrecy rate gains under CSI uncertainty (up to $\approx 15$ bps/Hz in high channel correlation configuration for the ZF-based projected channel scheme at SNR of 25 dB), over state-of-the-art approaches such as SVD-based and artificial-noise injection schemes.
Steve Sawadogo, Vincent Savaux, Luc Le Magoarou et al.· IEEE Open Journal of the Com...· 0 citations
