Research On Key Technology Of Cognitive Engine In Anti-jamming Communication

The current military operational environment interference problem even more serious,there have been many interference strategies for traditional anti-jamming technology.The development of new anti-jamming technology to ensure reliable military communications has become an important research topic.The idea of cognitive radio will be applied to anti-jamming communication areas through awareness of complex electromagnetic environment,the use of learning and intelligent decision-making methods to achieve efficient and reliable transmission of information,thus greatly improving the anti-jamming ability and spectrum utilization,which is the new trend of development of anti-interference communication.Aiming at this research direction,this paper is focus on design of cognitive engine and optimization of algorithm in the anti-jamming communication.Firstly,this paper analyzes the significance of cognitive radio technology application in anti-jamming communication,through introduction of status of home and abroad researches to show cutting-edge and feasibility of this topic.Thereafter,as the core technique of cognitive radio,cognitive engine plays an important role in the whole system and there is a detailed description of its existing engine architecture.We make a brief introduction of artificial intelligence algorithms commonly used in cognitive engine.Then it presents cognitive engine structure design of this paper using in frequency hopping communications.Moreover,the realization of cognitive engine functions in frequency hopping communication of this paper is introduced,focusing on the intelligent learning algorithm of cognitive engine and decision making of available spectrum resources to improve anti-jamming capability of the system.Through simulation of actual interference environment,communication experiment is carried out to verify the proposed system to achieve the purpose of reliable communications in noisy environment.After that,for the low convergence efficiency of traditional algorithms and easily to fall into local optimum,an improved simulated annealing particle swarm optimization(SABPSO)algorithm,which is the first time application in cognitive radio field,is present.It has greatly improved the convergence efficiency and adaptability value.The simulation proves that SABPSO is better than traditional algorithms on the convergence rate and average fitness,through the algorithm adaptively adjust carrier modulation scheme and transmit power.Finally,knowledge database as an important part of cognitive engine is described in detail.We study the design of cognitive anti-interference knowledge database and its internal logic structure,as a data storage center.