Swarm Intelligence Algorithm Assisted Dynamic Spectrum Sharing for UAV Swarm

This paper proposes a method for generating dynamic spectrum-sharing unmanned aerial vehicle (UAV) swarm formations based on the Swarm Intelligence Algorithm (SIA). It aims to address the challenges of limited spectrum resources and effective coordination. Utilizing a UAV swarm system model that considers node arrangement, spatial distribution, and wireless channels, we develop the SIA by integrating the Simulated Annealing-based Ant Colony Clustering (SAACC) algorithm for clustering and the Improved Grey Wolf Optimization (IGWO) algorithm for cluster head selection with optimization objectives focused on spectrum efficiency and fairness. By generating the initial formation through the K-means algorithm and iteratively applying SIA for clustering and cluster head selection, we establish the formation scheme. Numerical results demonstrate that the proposed SIA algorithm can rapidly generate a formation scheme for a dynamic spectrum-sharing UAV swarm, significantly enhancing spectral efficiency and fairness of UAV swarms with high efficiency and robustness.