A cognitive engine based on case-based reasoning quantum genetic algorithm

摘要

A cognitive engine is the key module of cognitive radio. To increase the speed of the cognitive engine, a case-based reasoning quantum genetic algorithm (CBR-QGA) is proposed. And a cognitive engine using CBR-QGA is presented to adjust and optimize the radio parameters. The environmental variation factor(EVF) is used to measure the similarity between the current problems and the storage cases. The initial quantum bit is composed of the parameters of the matching case and EVF so as to avoid the blindness of initial population searching and speed up the optimization of quantum genetic algorithm. Simulation results of multi-carrier system show that the proposed cognitive engine algorithm is much better than current algorithms in both the convergence rate and the optimization capability.