By analyzing engine decision of cognitive wireless network, the mathematical model of engine decision is given, and then it is converted into a multi-objective optimization problem. A Chaos quantum clonal algorithm is proposed to solve the problem, and the algorithm convergent with probability 1 is proved, in which the quantum coding and logistic mapping are used to initialize the population. A quantum mutation scheme is designed with chaotic disturbances. Finally, the simulation experiments are done to test the algorithm under a multi-carrier system. The results show that compared with QGA-CE (quantum genetic algorithm based cognitive engine), this algorithm has a good convergence and an objective function value. It can adapt the parameter configuration and meet the real-time requirement for cognitive engine.