关键词: 认知引擎, 二进制蚁群优化, 模拟退火, 认知无线电

Abstract: In cognitive radio system, cognitive engine can dynamically configure its working parameters according to the changes of communication environment and users’ requirement. Intelligent optimization algorithm of cognitive engine had been studied, and a Binary Ant Colony Simulated Annealing (BAC&SA) algorithm was proposed for parameters optimization of cognitive radio system. The new algorithm, which introduced the Simulated Annealing (SA) algorithm into the Binary Ant Colony Optimization (BACO) algorithm, combined the rapid optimization ability of BACO with probability jumping property of SA, and effectively avoided the defect of falling into local optimization result of BACO. The simulation results show that cognitive engine based on BAC&SA algorithm has considerable advantage over GA and BACO algorithm in the global search ability and average fitness.

Key words: Cognitive Engine, Binary Ant Colony Optimization (BACO), Simulated Annealing (SA), Cognitive Radio