A Novel Cognitive Radio Decision Engine Based on Chaotic Quantum Bee Colony Algorithm

Abstract

To improve the adaptive parameter adjustment function of the cognitive radio, a novel cognitive radio decision engine based on chaotic quantum bee colony optimized algorithm is proposed. First, the population was initialized by quantum coding and logistic mapping. Then, fast quantum rotation angle adjusting strategy, based on social cognitive, was used to conduct the neighborhood search of employed bees and onlooker bees. Finally, the new solution was generated by chaotic disturbing the solution that has reached the limit times of cycles. According to the simulated experiments under a multi-carrier system, the results indicate that the novel engine show a much better convergence and e‐ciency than the one based on quantum genetic algorithm or binary artiflcial bee colony algorithm, and the results of parameters reconflguration is consistent with user demands.