认知无线电中的量子蛙跳频谱分配

doi:10.3969/j.issn.0255-8297.2014.01.004

应用科学学报 ›› 2014, Vol. 32 ›› Issue (1): 19-26.doi: 10.3969/j.issn.0255-8297.2014.01.004

认知无线电中的量子蛙跳频谱分配

高洪元1，曹金龙2

1. 哈尔滨工程大学信息与通信工程学院，哈尔滨150001
2. 北京邮电大学信息与通信工程学院，北京100876

收稿日期:2011-11-08 修回日期:2012-05-29 出版日期:2014-01-31 发布日期:2012-05-29
作者简介:高洪元，博士，讲师，研究方向：无线通信系统、智能计算、雷达信号处理，E-mail: gaohongyuan@hrbeu.edu.cn
基金资助:
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

Quantum-Inspired Shuffled Frog Leaping Algorithm for Spectrum Allocation in Cognitive Radio

GAO Hong-yuan1, CAO Jin-long2

1. College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
2. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2011-11-08 Revised:2012-05-29 Online:2014-01-31 Published:2012-05-29

摘要/Abstract

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.

关键词: 量子蛙跳算法, 认知无线电, 频谱分配, 敏感图论着色, 网络效益

Abstract: To solve a discrete optimization problem, a quantum-inspired shuffled frog leaping (QSFL) algorithm based on shuffled frog leaping algorithm and quantum information theory is proposed. The QSFL algorithm uses quantum movement equations to find the optimal location by the co-evolution of quantum frog colony. Good performance of the QSFL algorithm is shown by some classical benchmark functions. At the same time, we design an assignment method for cognitive radio spectrum allocation without interference based on it. Simulations are conducted to compare this method with genetic algorithm (GA), quantum genetic algorithm (QGA), particle swarm optimization (PSO), shuffled frog leaping algorithm (SFLA) and color-sensitive graph coloring (CSGC) using different network utility functions. Simulation results indicate that the proposed method can find the near-optimal solution. It outperforms the color-sensitive graph coloring and the previous intelligent spectrum allocation methods.

Key words: quantum-inspired shuffled frog leaping algorithm, cognitive radio, spectrum allocation, colorsensitive graph coloring, network utility

中图分类号:

TN911.72，TP301.6

高洪元1，曹金龙2. 认知无线电中的量子蛙跳频谱分配[J]. 应用科学学报, 2014, 32(1): 19-26.

GAO Hong-yuan1, CAO Jin-long2. Quantum-Inspired Shuffled Frog Leaping Algorithm for Spectrum Allocation in Cognitive Radio[J]. Journal of Applied Sciences, 2014, 32(1): 19-26.

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认知无线电中的量子蛙跳频谱分配

Quantum-Inspired Shuffled Frog Leaping Algorithm for Spectrum Allocation in Cognitive Radio

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