Cross-layer Optimization Cognitive Decision Engine Synthesis of Particle Swarm Optimization and Differential Evolution

In order to solve the problem of parameter reconfiguration of the cognitive radio system， a cognitive decision engine (IPSODE) that combines particle swarm optimization and differential evolution is proposed. Firstly， an adaptive inertia weight mechanism is introduced into the PSO so that each individual adaptively evolves with individual fitness and its exploration capabilities improve. Then the crossover probability of DE improved， so as to improve the development ability of the algorithm. Finally， in the cognitive engine model， the populations that have evolved through PSO are divided into superior and inferior populations. The inferior populations use the modified DE to optimize and the individual differences of the particle population are increased. Simulations show that IPSO-DE enhances population development and exploration capabilities. Parameter optimization decision experiments of multi-carrier systems prove IPSO-DE algorithm’s effectiveness.