A Spatial-Functional Two-Dimensional Hierarchical Group Decision-Making Architecture for Spectrum Management of Emergency Communication UAV Swarms

This paper proposes a spatial-functional two-dimensional hierarchical group decision-making (HGDM) spectrum management architecture for emergency communication unmanned aerial systems (EC-UAS). The architecture handles the highly dynamic topology, large node population, and differentiated task priorities that characterize EC-UAS. Using the spectrum management properties of EC-UAS, we develop a discrete-time closed-loop dynamic model of the architecture and design adaptive hierarchical iteration rules. We prove global stability of the model under the stated assumptions and analyze the convergence of the state error, deriving its theoretical upper bound and the relationship between convergence steps and accuracy. An input-to-state stability analysis further demonstrates that the system state error remains bounded under dynamic disturbances, with its magnitude scaling with the disturbance bound. Simulations verify the effectiveness of the architecture and the correctness of the theoretical analysis.