2026· IEEE Journal on Selected Areas in Communications· Vol 44, pp. 5437-5449· 0 citations· 45 references
Computer Science
Abstract
The rapid development of uncrewed aerial vehicle (UAV) technology has brought security threats, which has motivated the development of integrated sensing and communication (ISAC) systems to address these issues. However, the power supply limitations of distributed ISAC nodes and the demand for covert signal transmission in adversarial scenarios remain unresolved. This paper focuses on covert transmission optimization for an integrated energy-harvesting, sensing and covert communication (IEHSCC) system, consisting of energy-harvesting (EH) nodes with switchable sensing/jamming modes and an ISAC base station (BS) to avoid detection by adversarial warden Willie. The minimum detection error probability (DEP) of Willie is derived, and the IEHSCC system’s sensing and covert transmission performance are calculated. Concerning the channel state information (CSI) estimation error, a joint optimization problem for EH node beamforming, BS beamforming, power allocation and EH node mode selection to maximize covert transmission rate is formulated. The problem is decomposed into subproblems and solved via S-Procedure and semi-definite relaxation (SDR) algorithm. An iterative water-filling algorithm is proposed to select EH modes. Simulation results show the proposed algorithm achieves fast convergence and effectively improves the covert transmission rate in the IEHSCC system. Increasing the number of antennas of EH node can increase covert rate, while excessive nodes or BS power degrades system performance, requiring rational configuration in practice.
—Unmanned aerial vehicles (UAVs) have been extensively deployed in wireless communication scenario. However, UAV communication faces the challenges of information leakage and energy limitation. Therefore, this paper studies energy-efficient covert communication in adversarial UAV-enabled wireless systems, where a UAV covertly delivers information to a legitimate ground receiver under the detection of a malicious detector with noise uncertainty. Our objective is to maximize covert energy efficiency, defined as the achievable covert throughput per unit of energy consumption, via the joint design of transmit power and flying location. To this end, we derive the detector’s minimum detection error probability to establish a covertness constraint. Based on this model, we formulate a three-dimensional joint optimization problem for transmit power and two-dimensional location, capturing the fundamental tradeoff among covertness, communication reliability, and energy efficiency. Through sys-tem geometric exploration, metric monotonicity analysis, and theoretical derivation, the original three-dimensional problem is reduced to a one-dimensional search over the flying angle, which enables efficient computation of the optimal UAV configuration via vectorized computation. Numerical results verify the theoretical derivations and illustrate the superiority of the joint design as well as the impact of system parameters on energy efficiency performance.
Yang-Fan Xu, Bin Yang, Yulong Shen et al.· IEEE Transactions on Dependa...· 0 citations
This paper investigates the energy consumption minimization problem of MIoT-oriented ISAC systems and builds a layered solution architecture that divides the original problem into independent subproblems and optimizes each alternately according to its mathematical features.
Integrated sensing and communication (ISAC) technology, when deployed on unmanned aerial vehicles (UAVs), enables aerial base stations to simultaneously provide wireless connectivity to ground users and perform environmental sensing through echo signal analysis. However, the broadcast nature of wireless transmission, combined with the line-of-sight (LoS) propagation characteristics of UAVs, increases the risk of passive eavesdropping on transmitted signals during ISAC missions. This paper investigates the joint trajectory design and power allocation (JTDPA) problem for UAV-enabled ISAC systems in environments with multiple mobile ground users and potential eavesdroppers. The proposed approach formulates the optimization problem as a constrained Markov decision process (CMDP), aiming to balance communication rate, secrecy rate, and energy consumption. To address the limitations of existing secure trajectory designs, such as unnecessary energy expenditure and overly conservative avoidance actions, we propose a two-stage (TS) strategy that incorporates the safe twin delayed deep deterministic policy gradient (Safe-TD3) algorithm, referred to as TS-SafeTD3. In the first stage (sensing stage), the UAV navigates toward a user-centric location without communication to enhance initial coverage efficiency, while satisfying the minimum-distance safety constraints with respect to potential eavesdroppers.In the second stage (ISAC stage), Safe-TD3 is employed to jointly optimize both trajectory and power allocation under the same safety constraints to maximize the weighted secrecy rate. Simulation results indicate that the proposed algorithm improves the weighted secrecy rate and energy efficiency under various operational conditions, while maintaining a low violation probability of the safety constraints.
Yu-Jia Chen, Hai-Yan Huang, Ting-Wei Chen et al.· IEEE Transactions on Network...· 0 citations
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 work investigates the performance trade-off among secure communication rate, radar estimation rate, and computational energy efficiency in an uncrewed aerial vehicle (UAV)-assisted ISCC system and focuses on maximizing the normalized weighted sum of the three performance metrics.
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
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