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.
Abstract
The integrated sensing, communication, and computing (ISCC) system overcomes the limitations of conventional standalone architectures. Through resource sharing and collaborative design, it dynamically optimizes and jointly enhances communication, sensing, and computing performance, thereby significantly improving overall system efficiency. 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. By jointly optimizing the UAV's three-dimensional (3D) trajectory, beamforming, user scheduling, and computational frequency, three optimization problems are formulated to maximize the average secrecy rate, sensing rate, and computational energy efficiency, respectively, thus establishing the system's performance boundaries under diverse scenarios. On this basis, the trade-off among security, sensing, and computation is further explored with the goal of maximizing the normalized weighted sum of the three performance metrics, which provides a theoretical basis for the performance-coordinated design of aerial ISCC systems.
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
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
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.
Wei-Wei Yang, Yutao Wang, Xinrong Guan et al.· IEEE Journal on Selected Are...· 0 citations
—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
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.
M. M. Selim, Mohamed Rihan, Armin Dekorsy et al.· IEEE Open Journal of the Com...· 0 citations
—Unmanned aerial vehicle (UAV) swarm-assisted integrated sensing and communication (ISAC) networks are a crucial technology for providing communication and sensing services in emergency rescue scenarios without base station support. However, the strong coupling between communication and sensing resources in such networks fundamentally limits the communication and sensing performance of ISAC systems. This paper jointly optimizes spectrum allocation, UAV association and deployment to maximize average system throughput while ensuring localization accuracy in such networks, where sensing is realized through localization. We begin by deriving an analytical expression for localization accuracy, which explicitly captures the joint effects of link quality and anchor geometry under shared communication-localization spectrum resources. We then formulate average system throughput maximization as a mixed-integer nonlinear and non-convex optimization problem with the constraints of localization accuracy, sub-channels, UAV association, UAV deployment and signal-to-interference-plus-noise ratio. We further develop an alternating iterative optimization method to solve this complex optimization problem. Within this method, a particle swarm optimization-based method is developed to jointly optimize spectrum allocation and UAV association, and a dueling double deep Q-network-based method is further employed for UAV deployment optimization. Finally, extensive simulation results are presented to validate the efficiency of our optimization method, and also to illustrate how key parameters influence average system throughput and localization accuracy.
Zhuo-Jia Yang, Wei Su, Bin Yang et al.· IEEE Transactions on Mobile...· 0 citations
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