Priority-Based Intelligent Scheduling Mechanism for Communication Resources in Multi-Kill Chains

The engagement sequence of kill chains is determined by the tactical threat level of targets, which in turn dictates the order of communication resource scheduling across multiple kill chains. Variations in communication requirements at different stages of a kill chain, coupled with enemy electromagnetic interference, pose significant challenges to resource scheduling. To address this, this paper defines resource scheduling priorities based on three dimensions: target type and distance. By leveraging deep reinforcement learning (DRL) to dynamically adjust Vickrey-Clarke-Groves (VCG) auction parameters, an adaptive elastic bandwidth constraint mechanism and dynamic payment pricing are achieved in complex electromagnetic environments. Simulation results demonstrate that the proposed algorithm outperforms comparative methods in terms of average reward and completion rate for high-threat targets, while also exhibiting superior stability under intensified interference.