2026· IEEE Transactions on Cognitive Communications and Networking· Vol 12, pp. 10372-10386· 0 citations· 62 references
Abstract
This paper investigates the rate-splitting multiple access (RSMA)-enabled integrated sensing, communication, and power transfer (ISCPT) network assisted by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). Particularly, considering the inherent heterogeneous quality-of-service (QoS) requirements, communication users (CUs) are granted priority in information reception, and the legitimate sensing targets (STs) are also regarded as potential eavesdroppers to intercept the information of CUs. In order to meet the service demands of heterogeneous users of such a system while ensuring the physical layer security of CUs against wiretapping, we formulate a secrecy energy efficiency (SEE) maximization problem via jointly optimizing the transmit beamforming matrix, sensing matrix, STAR-RIS reflection/transmission coefficient matrix, power splitting (PS) ratio vector, and common rate allocation vector. Due to the non-convexity of the formulated problem and the challenges caused by imperfect channel state information (CSI) and dynamic wireless environment, an agentic-AI enabled optimization approach (ISCPT-SEE-AA) is proposed, which works in a closed-loop perception-decision–reward adaptation manner. Specifically, a Transformer-based channel refinement module is developed to mitigate the uncertainty induced by imperfect CSI. Meanwhile, a mixture-of-experts group relative policy optimization (MoE-GRPO) scheme is adopted to achieve adaptive decision-making under time-varying network conditions. Furthermore, a large language model (LLM)-aided reward configuration module with retrieval-augmented generation (RAG) is integrated to automatically configure and update reward parameters, thereby reducing manual tuning overhead and enhancing training stability. Extensive simulation results verify that the proposed ISCPT-SEE-AA outperforms conventional learning-based schemes significantly in terms of SEE and exhibits stronger robustness against CSI imperfections. Notably, it achieves performance close to that of the convex optimization-based benchmark with substantially lower online computational complexity.
In this paper, we investigate the covert communication performance and sensing performance of integrated sensing and communication (ISAC) systems enhanced by simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). A novel non-orthogonal multiple access (NOMA) enabled covert framework is proposed, where the covert transmission can be enhanced by eliminating the interference of public signals and sensing signals at the covert user. The large system analytic estimation is employed to effectively decouple the correlation of the warden’s channel fading gains and derive a closed-form expression for the minimum average detection error probability of the warden. Both sensing and covert rate optimization problems are investigated through jointly designing base station transmit beamforming and STAR-RIS passive beamforming. To optimize sensing performance, we aim at minimizing the Cramér-Rao bound (CRB) while satisfying the covert rate requirement. Conversely, when maximizing the covert rate, the CRB is incorporated as a constraint in the sensing. To address these challenging optimization problems, an iterative algorithm based on penalty methods and semidefinite programming are proposed to obtain the transmit beamforming and the beamforming of STAR-RIS. Simulation results indicate that the CRB and covert rate of the proposed ISAC systems, assisted by STAR-RIS and NOMA, outperform the ISAC systems enhanced by orthogonal multiple access and conventional RIS.
Zheng Yang, Haoyang Li, Gaojie Chen et al.· IEEE Transactions on Wireles...· 0 citations
This paper investigates a reconfigurable intelligent surface (RIS)-assisted secure non-orthogonal multiple access (NOMA) network in the presence of both internal eavesdroppers (IEs) and external eavesdroppers (EEs). To mitigate threats of IEs, a reversed successive interference cancellation (SIC) decoding order is adopted. Maximizing the sum secrecy rate is framed as a non-convex optimization challenge, where the primary decision variables are the RIS phase shifts and the transmit precoding matrix. A soft actor-critic (SAC)-based deep reinforcement learning (DRL) scheme is developed to solve this problem. Numerical results verify that the proposed scheme surpasses deep deterministic policy gradient (DDPG) and exceeds conventional successive convex approximation (SCA) at low transmit power. It also converges faster and operates more stably than the DDPG-based approach.
Chengxue Liu, Xueliang Shi, Junyu Tan et al.· International Conference on...· 0 citations
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.
Yifeng Zhao, Hongzheng Wang, Peng Lu et al.· ACM transactions on sensor n...· 0 citations
This paper investigates a reconfigurable-intelligent-surface (RIS)-aided simultaneous-wireless-information-and-power-transfer (SWIPT) system, which can be utilized in crisis-resilient scenarios. Specifically, a passive RIS is deployed to facilitate both data transmission for information users (IUs), e.g., the response team, and wireless power delivery for energy devices (EDs), e.g., wireless sensors and wearable devices. In the considered RIS-assisted SWIPT system, the active beamforming vectors at the base station and the passive phase-shift vectors at the RIS are jointly optimized with the objective of minimizing the total transmit power subject to three critical constraints: i) guaranteeing quality-of-service requirements of the IUs to ensure reliable communications, ii) satisfying the required power demands of EDs for uninterrupted operation, and iii) preserving the passive characteristics of the RIS. The resulting optimization problem is non-convex and multivariate, rendering it NP-hard. To address this challenge, a bio-inspired firefly algorithm (FFA) is developed to obtain near-optimal solutions. Numerical results demonstrate that the proposed FFA-based approach achieves significant transmit power savings and outperforms conventional alternating optimization techniques in both solution quality and scalability.
Simulation results demonstrate the effectiveness of the proposed framework and show that the BD-RIS-assisted system achieves up to a 45.2% sum-rate improvement compared with conventional single-connected RIS (SC-RIS) architectures while maintaining robustness against CSI uncertainty and satisfying all system constraints.
Zain Ali, Muhammad Asif, S. Althunibat et al.· IEEE Access· 0 citations
Motivated by the increasing security requirements of next-generation satellite-terrestrial communication systems and the emergence of Open Radio Access Network (O-RAN) architectures, this paper presents a secrecy analysis of a novel reconfigurable intelligent surface (RIS)-assisted mixed free-space optical (FSO) and radio frequency (RF) satellite downlink transmission system within an O-RAN-enabled non-terrestrial network (NTN) framework. The inherent broadcast nature of RF transmissions presents significant eavesdropping risks, which serves as the primary impetus for this study. We analyze the combined effects of imperfect channel state information (CSI) and random link blockage within such integrated networks. The impact of discrete phase shift constraints at the RIS is also investigated. Closed-form expressions are derived for three key performance metrics: connection outage probability (COP), secrecy outage probability (SOP), and the probability of positive secrecy capacity (PPSC). Through high signal-to-noise ratio (SNR) asymptotic analysis, corresponding asymptotic expressions are obtained, and all analytical results are validated via extensive Monte Carlo simulations. Our findings demonstrate that: (i) Link blockage probability and channel estimation accuracy jointly govern the secrecy performance floor. (ii) Increasing the number of RIS elements enhances physical-layer security by driving both the COP and SOP toward their theoretical lower bounds. (iii) Improving channel estimation accuracy diminishes the eavesdropper’s channel advantage and improves the overall system security. These results offer valuable insights for designing secure mixed FSO/RF satellite-terrestrial systems within O-RAN-enabled NTN architectures that effectively balance connectivity and confidentiality.
Yuhang Li, Xi-Fan Chen, Jiale Shi et al.· Entropy· 0 citations
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