A dynamic spectrum and power allocation method for co-located pulse radar and communication system coexistence

Airborne pulse radar and communication systems are essential for precise detection and collision avoidance, ensuring that aircraft operate safely and efficiently. A major challenge in spectrum sharing is the allocation of resources in both the time and frequency domains, aiming to minimize inter-system interference as the available spectrum fluctuates over time. In this paper, regarding maximization of detection probability and spectrum utilization efficiency as two fundamental objectives, a novel Dynamic Spectrum and Power Allocation based on Genetic Algorithm (GA-DSPA) model is proposed, which dynamically allocates communication channel frequency and power under the constraints of pulse radar detection probability and signal-to-interference-plus-noise ratio of communication. To solve this bi-objective model, a non-dominated sorting-based multi-objective genetic algorithm is developed. A novel environment perception strategy and offspring sorting technique based on radar echoes are integrated into the optimization framework. Simulation results indicate that by integrating environmental monitoring mechanisms and dynamic adaptation strategies, the proposed method effectively tracks the evolving Pareto-optimal Fronts (PoFs), thereby ensuring optimal performance for both co-located pulse radar and communication systems. Hardware test results confirm that within the GA-DSPA framework, the pulse radar achieves higher detection probabilities under identical conditions, while the communication system realizes increased average throughput.