认知无线电中的量子蛙跳频谱分配

发布时间：2018-03-04 16:26

本文选题：量子蛙跳算法　切入点：认知无线电　出处：《应用科学学报》2014年01期 　论文类型：期刊论文

【摘要】：为了有效求解离散优化问题,将量子信息理论引入混合蛙跳算法,提出一种新的组合优化算法——量子蛙跳算法.量子蛙跳算法使用新的量子跳跃方程完成整个量子蛙群的协同演进,能快速搜索到全局最优位置.通过对基准函数的测试验证了其高效性,并使用量子蛙跳算法设计了一种认知无线电频谱分配算法.通过仿真实验对比了所提出的量子蛙跳算法与遗传算法、量子遗传算法、粒子群算法、混合蛙跳算法和敏感图论着色算法等多种算法在不同网络效益函数下实现频谱分配的性能.在3种网络效益函数下进行的仿真结果表明,所提出的算法能较好地找到最优解,且在不同的网络效益函数下均优于已有的敏感图论着色频谱分配算法和智能频谱分配算法.
[Abstract]:In order to solve the discrete optimization problem effectively, the quantum information theory is introduced into the hybrid leapfrog algorithm. A new combinatorial optimization algorithm, quantum leapfrog algorithm, is proposed. The quantum leapfrog algorithm uses a new quantum jump equation to complete the cooperative evolution of the whole quantum frog population. Can quickly search the global optimal location. The benchmark function is proved to be efficient by testing. A spectrum allocation algorithm for cognitive radio is designed by using quantum leapfrog algorithm. The proposed quantum leapfrog algorithm is compared with genetic algorithm, quantum genetic algorithm and particle swarm optimization algorithm. Hybrid leapfrog algorithm and sensitive graph theory coloring algorithm are used to achieve spectrum allocation performance under different network benefit functions. The simulation results under three network benefit functions show that the proposed algorithm can find the best solution. Moreover, it is superior to the existing sensitive graph theory coloring spectrum allocation algorithm and intelligent spectrum allocation algorithm under different network benefit functions.
【作者单位】：哈尔滨工程大学信息与通信工程学院;北京邮电大学信息与通信工程学院;
【基金】：国家自然科学基金(No.61102105;No.61102106) 中国博士后科学基金(No.2013M530148) 中央高校基本科研业务费专项基金(No.HEUCF100801)资助
【分类号】：TN925

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