UAV-Enabled Covert Wireless Data Collection
Xiaobo Zhou, Shihao Yan, Feng Shu, Riqing Chen, Jun Li

TL;DR
This paper proposes a novel UAV-based covert data collection system that jointly optimizes trajectory, artificial noise, and user scheduling to maximize transmission rates while maintaining covertness, solved via a penalty convex approximation scheme.
Contribution
It introduces a joint design framework for UAV trajectory, artificial noise, and user scheduling under covertness constraints, solved with a new penalty successive convex approximation method.
Findings
The proposed P-SCA scheme outperforms benchmark schemes in max-min average transmission rate.
A new UAV trajectory initialization based on the Successive Hover-and-Fly scheme.
Effective joint optimization enhances covert data collection performance.
Abstract
This work considers unmanned aerial vehicle (UAV) networks for collecting data covertly from ground users. The full-duplex UAV intends to gather critical information from a scheduled user (SU) through wireless communication and generate artificial noise (AN) with random transmit power in order to ensure a negligible probability of the SU's transmission being detected by the unscheduled users (USUs). To enhance the system performance, we jointly design the UAV's trajectory and its maximum AN transmit power together with the user scheduling strategy subject to practical constraints, e.g., a covertness constraint, which is explicitly determined by analyzing each USU's detection performance, and a binary constraint induced by user scheduling. The formulated design problem is a mixed-integer non-convex optimization problem, which is challenging to solve directly, but tackled by our developed…
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Taxonomy
TopicsUAV Applications and Optimization · Wireless Communication Security Techniques · Ethics and Legal Issues in Pediatric Healthcare
