UAV-Aided Data Collection Against Detection: Joint Trajectory and User Scheduling Design

IEEE Transactions on Vehicular Technology, vol. 74, pp. 14817–14822

Abstract

We consider an unmanned aerial vehicle (UAV)- aided covert data collection against detection from a malicious warden with uncertain location and provide the joint UAV trajectory and user scheduling design to minimize task completion time. Particularly, we first derive the closed-form expressions for covert data collection metric and the maximum transmit power follows covertness constraint for warden at any possible location, based on which a joint continuous trajectory and user scheduling design problem is formulated which introduces significant challenges for handling highly complex problems involving infinite variables. Then, based on the optimal successive-hover-and-fly (SHF) structure, we successfully construct the reformulation the problem containing finite variables without loss of optimality. And an efficient iteration algorithm based proposed rigorous convex approximation is developed to solve the reformulation problem efficiently. Numerical results show that the proposed scheme significantly outperforms the conventional benchmark in completion time minimization and computing time reduction.

Authors 5

1. Peng Wu

   Wuhan University

   Affiliation as printed

   School of Electronic Information, Wuhan University, Wuhan, China

2. Kaihong Li

   Wuhan University

   Affiliation as printed

   School of Electronic Information, Wuhan University, Wuhan, China

3. Xiaopeng Yuan Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   Chair of Information Theory and Data Analytics, RWTH Aachen University, Aachen, Germany

4. Yulin Hu

   Wuhan University

   Affiliation as printed

   School of Electronic Information, Wuhan University, Wuhan, China

5. Anke Schmeink Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   Chair of Information Theory and Data Analytics, RWTH Aachen University, Aachen, Germany