Digital Twin-Enabled Task-Driven UAV Communications Under Uncertainty

Efficient task information interaction is the key to unmanned aerial vehicle (UAV) swarm collaboration. However, the driving force of both the spatial-temporal correlation and physical-virtual interaction has not been fully considered in existing works. In this paper, we aim to utilize the advanced digital twin technology to realize the efficient information interaction between the physical and virtual layers for UAV swarm collaboratively performing various tasks. Considering the driving force of both task correlation and transmission timeliness, the physical-virtual interaction link selection problem is formulated under uncertain estimation deviations in the form of interval number. To address this challenging problem, we first utilize the interval optimization for transforming the uncertain utility values to the certain preference orderings in matching theory, and then propose an interval rank-maximal matching algorithm to make predictive link selection based on unilateral preference information. Simulation results confirm that our proposed method can improve the interaction efficiency significantly under uncertainty.