基于组合混沌遗传算法的认知无线电资源分配

摘要

提出了基于组合混沌遗传算法用于认知无线电资源分配，设计了相应的组合混沌序列发生器，并分别运用组合混沌遗传算法、粒子群优化算法、模拟退火算法及简单遗传算法对认知无线电资源分配问题进行了仿真分析．结果表明，组合混沌遗传算法具有收敛速度快、搜索空间广、全局收敛等优点．相比其他三种算法，基于组合混沌遗传算法进行资源分配提高了认知无线电系统的传输速率，降低了系统的发射功率及误码率，同时加快了收敛速度．%The combined chaotic genetic algorithm for cognitive radio resource allocation is proposed, and corresponding combined chaotic sequence generator is designed. Simulations are conducted by using the combined chaotic genetic algorithm, the particle swarm optimization algorithm, the simulated annealing algorithm, and the simple genetic algorithm, thereby analyzing the multi-users, cognitive radio resource allocation. The results show that the combined chaotic genetic algorithm has advantages of fast convergence rate, vast search space and global convergence. The combined chaotic genetic algorithm has better performance than the other three algorithms in terms of cognitive radio resource allocation, there by reducing the bit error rate and the transmission power consumption of the system. Besides, it also has a faster convergence rate.