Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) have emerged as a transformative technology for achieving omnidirectional coverage in smart radio environments, enabling energy-efficient and spectrally efficient wireless communications. When integrated with ambient backscatter communication (AmBC) and non-orthogonal multiple access (NOMA), STAR-RIS facilitates the concurrent exploitation of ambient radio frequency signals and spectrum resources, offering significant potential for scalable Internet of Things (IoT) networks. This paper conducts a comprehensive analysis of the physical layer security performance of a STAR-RIS-assisted AmBC system employing NOMA in the presence of multiple eavesdroppers. Specifically, the STAR-RIS serves as an active backscatter device to enhance the backscatter link by mitigating direct link interference, while NOMA optimizes spectrum utilization through power-domain multiplexing. We derive closed-form expressions for critical performance metrics, including outage probability (OP), intercept probability, throughput, and energy efficiency, under realistic channel fading models. Asymptotic analysis of the OP is provided to reveal insights into high signal-to-noise ratio regimes. Furthermore, we investigate the impact of key system parameters. Numerical results validate that the proposed STAR-RIS-assisted AmBC-NOMA framework significantly enhances secrecy performance compared to conventional AmBC systems, demonstrating its robustness against eavesdropping threats and its suitability for secure IoT applications.
Yuhui Zhou, Gaojian Huang, Xingwang Li et al.· IEEE Transactions on Cogniti...· 0 citations
Integrated Sensing and Communication (ISAC) is emerging as a key technology for next-generation wireless networks, enabling simultaneous communication and sensing functionalities. This paper focuses a RIS-assisted full-duplex (FD) ISAC system, in which a multi-antenna base station (BS) concurrently performs multi-user uplink and downlink transmission while also carrying out radar sensing. To maximize the joint uplink–downlink sum rate, an optimization problem is formulated under practical constraints, such as radar detection SINR, self-interference, BS transmit power, user power budgets, and RIS unit-modulus conditions. To address the nonconvexity of this problem, a two-stage hybrid optimization approach is developed. In the first stage, the augmented Lagrangian technique decomposes the complex problem into simpler subproblems involving beamforming, power allocation, and RIS phase optimization, leading to a feasible initial solution. The second stage employs a Multi-Agent Deep Deterministic Policy Gradient (MADDPG) framework to refine this solution adaptively, enabling the system to respond effectively to variations in the channel environment, mobility patterns, and interference levels. The proposed hybrid framework achieves optimal resource allocation while maintaining feasibility, robustness, and adaptability. Analytical results confirm its convergence behavior, and extensive simulation results confirm that the proposed scheme consistently outperforms conventional optimization and single-agent DRL baselines in sum-rate maximization, interference mitigation, and sensing accuracy, confirming its effectiveness for RIS-assisted full-duplex ISAC systems.
S. Waqas, Fenghua Huang, Fakhar Abbas et al.· IEEE Transactions on Wireles...· 0 citations
