2026· IEEE Transactions on Wireless Communications· Vol 25, pp. 21814-21829· 0 citations· 44 references
Abstract
A pinching-antenna system (PASS)-enabled multi-UAV integrated sensing and communication (ISAC) framework is proposed for adaptive downlink communications and UAV sensing. By jointly optimizing the pinching antenna (PA) activation, waveguide-level baseband precoding, and PA-level radiation power, the weighted sum of communication rates and sensing information rates is maximized, subject to the minimum-rate requirements of communication users (CUs) and sensing targets (STs). To address the resulting mixed-integer, high-dimensional, and strongly coupled non-convex problem, a genetic algorithm (GA)-based two-layer optimization (TLO) framework is developed. The PA activation is inferred by a GA-trained MLP policy in the outer layer, while the waveguide-level baseband precoding and PA-level radiation power are alternately optimized using weighted minimum mean-square error (WMMSE) and successive convex approximation (SCA) in the inner layer. Numerical results demonstrate that the proposed GA-TLO significantly improves both weighted sum rate and constraint satisfaction compared with conventional multiple-antenna architectures. Moreover, it achieves up to a 35% higher weighted sum rate than the fixed-activation PASS benchmark with BCD-based continuous optimization, while also substantially outperforming the fully uniform PASS and MIMO baselines.
An unmanned aerial vehicle (UAV)-enabled ISAC system employing rate-splitting multiple access (RSMA) and a joint beamforming and trajectory optimization framework is investigated and results demonstrate that the proposed algorithm significantly improves the achievable system downlink rate.
Shunxuan Wang, Qi Zhu· Italian National Conference...· 0 citations
Simulation results demonstrate that the proposed method significantly reduces the time-averaged CRB by over 10%, compared with the ISAC system without UAV assistance, and also achieves a higher sensing accuracy than both the fixed-UAV-trajectory and the maximum-ratio-transmission-based beamforming benchmarks.
This survey provides a systematic review across six interconnected domains—channel estimation (CE) and beam tracking, throughput maximization, weighted sum rate (WSR) and sensing co-optimization, delay and age of information (AoI) minimization, energy efficiency (EE), and PLS—each supported by a structured comparative table covering over 80 methodologies.
Manzoor Ahmed, Syed Tariq Shah, A. A. Nasir et al.· IEEE Open Journal of the Com...· 1 citation
This work investigates the secrecy performance of a dual-uncrewed aerial vehicle (UAV)-assisted secure ISAC system, and maximizes the average secrecy rate by optimizing user scheduling strategies, time allocation, transmit power, and UAV trajectories.
Hongjiang Lei, Jianshuo Geng, Ki-Hong Park et al.· 1 citation
This paper proposes a novel physical-layer security framework for multi-UAV Integrated Sensing and Communication (ISAC) networks operating in adversarial environments. To maximize the sum secrecy rate of legitimate ground users (GUs) while satisfying minimum sensing beampattern-gain constraints for target illumination, we introduce a dynamic role allocation mechanism in which each UAV can switch, on a per-time-slot basis, between an ISAC mode—combining coherent communications with radar sensing—and a dedicated artificial noise (AN) jammer mode. The resulting optimization is cast as a highly coupled Mixed-Integer Non-Linear Program (MINLP) that jointly optimizes binary role indicators, transmit beamforming and sensing covariance matrices, and UAV trajectories. We solve this problem with a tailored Alternating Optimization (AO) algorithm that integrates a penalty-based Convex-Concave Procedure (CCP) for the binary role subproblem, Semidefinite Relaxation (SDR) for the beamforming subproblem, and a trust-region Successive Convex Approximation (SCA) for the trajectory subproblem. Numerical results demonstrate that the proposed dynamic-role architecture consistently outperforms both a static dedicated-jammer scheme and a fully optimized all-ISAC embedded-AN benchmark, confirming that its secrecy advantage arises from adaptive spatial-functional specialization rather than from artificial-noise transmission alone. Furthermore, we characterize the fundamental tradeoff between secrecy performance and stringent sensing beampattern-gain constraints, showing that moderate sensing requirements can be accommodated with no secrecy penalty.
M. M. Selim, Mohamed Rihan, Armin Dekorsy et al.· IEEE Open Journal of the Com...· 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
