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Joint UAV trajectory and offloading optimization with robust secrecy for intelligent mining.

Abdulbasit A Darem1, Khalid Almalki2, Abdulrahman Alzahrani3

  • 1Center for Scientific Research and Entrepreneurship, Northern Border University, Arar, 73213, Saudi Arabia.

Scientific Reports
|May 30, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a dual-edge architecture for secure, energy-efficient aerial communication in intelligent mining. The optimized jammer UAV trajectory significantly enhances energy efficiency and security against eavesdroppers.

Keywords:
Aerial-edge computingBlock coordinate descentCooperative jammingDinkelbach transformFDMAIntelligent miningRobust physical-layer secrecyRotary-wing propulsionSuccessive convex approximationUAV trajectory optimization

Related Experiment Videos

Area of Science:

  • Wireless Communications
  • Edge Computing
  • Network Security

Background:

  • Intelligent mining requires real-time UAV sensor data processing under strict latency, safety, and energy constraints.
  • Existing solutions struggle to balance performance, security, and energy efficiency in dynamic aerial environments.
  • Aerial communication systems face challenges from channel fading, eavesdropping, and limited energy resources.

Purpose of the Study:

  • To develop a robust dual-edge architecture for secure and energy-efficient aerial communication in intelligent mining.
  • To maximize energy efficiency while ensuring data security against passive eavesdroppers with location uncertainty.
  • To optimize the trajectory of a jammer UAV for enhanced security and communication performance.

Main Methods:

  • A dual-edge architecture combining a ground base station (BS) and an aerial edge server (AES) serving aerial users (FDMA).
  • Modeling of 3GPP A2G channels, including probabilistic line-of-sight/non-line-of-sight (LoS/NLoS) and state-conditioned fading.
  • A robust optimization framework maximizing energy efficiency by considering worst-case eavesdropper rates and employing convex optimization techniques (Dinkelbach, BCD, SCA, micro-AO).

Main Results:

  • The proposed scheme achieves 60.5 kbits/J, outperforming existing methods (STRO by 22.2%, SHJ by 116.1%).
  • The system demonstrates resilience to eavesdropper location uncertainty, with only a 13.1% degradation in energy efficiency.
  • Optimized jammer trajectory enhances jamming geometry, with propulsion being the dominant energy consumer (86.8%).

Conclusions:

  • The developed dual-edge architecture provides a feasible near-real-time solution for secure and energy-efficient data offloading in intelligent mining.
  • Robust optimization is crucial for maintaining performance and security under eavesdropping threats and location uncertainties.
  • Trajectory optimization of jammer UAVs is essential for effective physical layer security in aerial communication networks.