An optimization problem to maximize the total secrecy rate of all users while ensuring that the radar sensing performance satisfies a required minimum signal-to-noise ratio (SNR) is formulated and an iterative algorithm based on the alternating optimization framework is developed, which reduces computational complexity.
Abstract
The amalgamation of Reconfigurable Intelligent Surface (RIS) and Non-Orthogonal Multiple Access (NOMA) within Integrated Sensing and Communication (ISAC) frameworks is a key enabler to enhance spectral efficiency in 6G networks. Nevertheless, the broadcast nature of dual-functional signals that simultaneously support communication and sensing introduces physical-layer security vulnerabilities, especially in sensor networks. This paper addresses this critical challenge by investigating secure beamforming design in an RIS-NOMA-ISAC system. We formulate an optimization problem to maximize the total secrecy rate of all users while ensuring that the radar sensing performance satisfies a required minimum signal-to-noise ratio (SNR). To tackle this non-convex problem, we develop an iterative algorithm based on the alternating optimization (AO) framework, which reduces computational complexity. Specifically, the secrecy rate maximization problem is decomposed into two subproblems. The non-convex objective function and constraints are handled by the successive convex approximation (SCA) technique, which transforms them into a series of second-order cone constraints and linear constraints. As a result, the originally non-convex problem is converted into a convex one that can be efficiently solved. Simulation results demonstrate that the proposed algorithm achieves satisfactory security performance while ensuring effective radar sensing, and outperforms benchmark schemes with random RIS phase shifts and without RIS assistance.
An alternating optimization (AO) framework is proposed, employing techniques including discrete binary particle swarm optimization (BPSO), successive convex approximation (SCA) and difference-of-convex (DC) programming to transform the optimization problem into convex subproblems.
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This paper investigates secure beamforming designs for integrated sensing and communication (ISAC) systems, where a base station (BS) provides downlink and uplink communication services while performing target sensing, under both passive eavesdropping and active malicious jamming. To address these threats, a comprehens...
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Simulation results demonstrate that compared with benchmark schemes, the proposed algorithm can better guarantee the secrecy rate and effectively track the moving trajectory of the eavesdropper.
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