DOI: 10.3390/drones7090562 ISSN:

UAV Digital Twin Based Wireless Channel Modeling for 6G Green IoT

Fei Qi, Weiliang Xie, Lei Liu, Tao Hong, Fanqin Zhou
  • Artificial Intelligence
  • Computer Science Applications
  • Aerospace Engineering
  • Information Systems
  • Control and Systems Engineering

This paper explores the advancements of drones in the context of sixth-generation mobile communication technology (6G) green Internet of Things (IoT) through the utilization of digital twin (DT) technology within unmanned aerial vehicle (UAV) networks. We propose a framework for DT-based UAV applications in the realm of green IoT, where distinct tasks within the digital twin interact with physical-world UAVs through task manager scheduling. We characterize the radio frequency (RF) attributes of the DT using three-dimensional (3D) millimeter-wave (mmWave) radar imaging on UAVs. The wireless channel modeling, based on ray tracing, underscores the alignment of RF domains between the DT and the physical UAV in a bid to take advantage of multipath reflections and save communication energy. Our numerical findings have justified the efficacy of the drone-enabled DT platform in achieving accurate RF representation of UAVs for the intelligent operation and management of IoT-based green UAV networks.

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