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Joint Trajectory Design and Power Optimization in Adversarial UAV Communications: A Game Theory Framework

  • Jinyue Liu
  • , Peng Gong
  • , Haowei Yang
  • , Jihao Zhang
  • , Liehuang Zhu
  • , Xiang Gao*
  • *Corresponding author for this work
  • Beijing Institute of Technology
  • Institute of Computer Application Technology

Research output: Contribution to journalArticlepeer-review

Abstract

To address the challenges of dynamic jamming and resource optimization in uncrewed aerial vehicle (UAV) confrontation communication networks, this article proposes a hierarchical game framework for joint trajectory design and power allocation. These elements are inherently coupled: jamming degrades channel quality, prompting UAVs to adapt both their trajectories to improve spatial positioning and reduce jamming exposure, and their power allocation to maintain communication effectiveness under interference. The framework captures this interplay through a differential game for trajectory optimization and a Stackelberg game for power allocation, with the Nash equilibrium (NE) rigorously defined and its existence proved. To overcome the complexity of solving the Hamilton–Jacobi–Bellman (HJB) equation, an adaptive dynamic programming (ADP) algorithm is employed to approximate the value functions for both trajectory and power optimization. Simulations validate the effectiveness of the proposed framework, demonstrating that it accurately captures the strategic interactions between UAVs and provides robust decision support for resource optimization in dynamic adversarial environments.

Original languageEnglish
Pages (from-to)6808-6823
Number of pages16
JournalIEEE Internet of Things Journal
Volume13
Issue number4
DOIs
Publication statusPublished - 2026
Externally publishedYes

Keywords

  • Adaptive dynamic programming (ADP)
  • Stackelberg game
  • anti-jamming
  • differential game
  • uncrewed aerial vehicle (UAV)

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