Cognitive Anti-jamming Intelligent Decision Based on Improved Artificial Bee Colony Algorithm

Intelligent decision-making is the core of the cognitive anti-jamming system, the optimal decision is made on the system’s jamming suppression mode, spectrum resource allocation, modulation and coding mode and power adjustment information according to the jamming environment. Compared with other swarm intelligence algorithms, Artificial Bee Colony(ABC) has faster global optimization, less parameter setting and more flexibility, and it is easy to combine with other technologies to improve the original algorithm. It is more practical, but ABC algorithm also has its limitations, such as weak local search ability, slow convergence in the later period. For the decision of discrete parameters in complex interference environments, this paper designs an intelligent anti-interference intelligence decision engine based on improved artificial bee colony algorithm, analyzes the engine model, designs the objective function and chromosome based on the system efficiency, elaborates the decision-making steps, optimizes the decision-making parameters and proposes an improved algorithm based on genome search. Through the system anti-jamming performance simulation, it is verified that compared with the anti-jamming system without intelligent decision engine, the cognitive anti-jamming system using the intelligent decision engine proposed in this paper not only has strong anti-jamming performance in the interference environment, but also has lower transmission power and higher transmission efficiency on the premise of guaranteeing the reliability of communication transmission. Compared with decision engine using original artificial bee colony algorithms and genetic algorithm, the decision engine based on improved artificial bee colony algorithm has fewer average convergence algebras and higher optimal solution probability.