混沌量子克隆算法求解认知无线网络频谱分配问题

对认知无线网络中的频谱进行有效分配是实现动态频谱接入的关键技术.考虑3次用户对频谱的需求和分配的公平性,给出了频谱分配的数学模型,并将其转换为以最大化网络收益为目标的带约束优化问题,进而提出一种采用混沌量子克隆优化求解的认知无线网络频谱分配算法, 并证明了该算法以概率1收敛.最后,通过仿真实验比较了本文算法与颜色敏感图着色算法、基于遗传算法的频谱分配、基于量子遗传算法的频谱分配的性能.结果表明:本文算法性能较优, 能更好地实现网络收益最大化.关键词：混沌量子克隆算法认知无线网络频谱分配

Chaos quantum clonal algorithm for spectrum allocation of cognitive wireless network

Efficient spectrum allocation of cognitive wireless network is the key technology to dynamic spectrum access. Taking into account the needs of secondary users for the spectrum and the fairness allocation of the spectrum, mathematical model of spectrum allocation is given, and then it is converted into a constrained optimization problem with the goal of maximizing network profits. A chaos quantum clonal optimization algorithm is proposed to solve the problem, and then the convergence of the algorithm with probability 1 is proved. Finally, the simulation experiments are done to test the algorithm. The results show that compared with the color-sensitive graph coloring algorithm, the spectrum allocation based on genetic algorithm, and the spectrum allocation based on quantum-inspired genetic algorithm, the algorithm has good performances. It can achieve the maximization of network profits.