A Data Link Slot Allocation Algorithm Based on Improved Particle Swarm Optimization

Tactical data link systems commonly employ Time Division Multiple Access (TDMA) network access methods. Slot allocation technology plays a crucial role in TDMA system. Existing slot allocation algorithms often suffer from insufficient global search capabilities, high computational demands, and low efficiency. This paper proposes an improved particle swarm optimization algorithm based on an adaptive weight mechanism. By dynamically adjusting the inertia weight, the algorithm not only prevents premature convergence caused by improper weight settings but also ensures effective exploration of the solution space during iterations, accelerating convergence in the later stages and enhancing the algorithm's global search capability. Experimental results demonstrate that compared to traditional PSO slot allocation algorithms and other slot allocation methods, the proposed adaptive weight particle swarm optimization algorithm ensures high stability and can rapidly find the most uniform and optimal slot allocation scheme for nodes, thereby enhancing slot resource utilization and effectively reducing end-to-end transmission delay jitter.