改进的细菌觅食算法求解认知无线网络频谱分配问题  

Cognitive Radio Spectrum Assignment Based on Binary Bacterial Foraging Optimization Algorithm

作　　者：李岳洪[1] 万频[1] 王永华[1,2] 邓钦[1] 杨健[1] 

机构地区：[1]广东工业大学自动化学院,广州510006 [2]深圳市高性能数据挖掘重点实验室,深圳518055

出　　处：《计算机科学》2013年第8期49-52,58,共5页Computer Science

基　　金：国家自然科学基金(61172156;61102034);深圳市生物;互联网;新能源产业发展专项资金(CXB201005250021A);广东工业大学博士启动基金(103042);广东工业大学团队平台重大成果培育基金项目(GDUT2011-10)资助

摘　　要：认知无线网络中如何进行频谱合理的分配是实现动态频谱接入的关键技术之一。基于图论着色频谱分配模型,以最大化网络效益为目标函数,提出一种具有量子变异操作的改进的二进制细菌觅食优化算法,用以求解认知无线网络中空闲频谱在认知用户间的动态分配问题。通过仿真实验比较了本算法与颜色敏感图论着色算法、传统二进制细菌觅食算法的性能。结果表明:本算法性能明显优于颜色敏感图论着色算法,能更好地实现网络效益最大化,提高用户的平均效益;与传统二进制细菌觅食算法相比,改进后的细菌觅食算法寻优能力更强,收敛速度更快。How to make efficient spectrum allocation of cognitive wireless network is the key technology for dynamic spectrum access. This paper presented an improved binary bacterial foraging optimization algorithm with quantum varia- tion operation based on the graph coloring theory model of spectrum assignment, and used the maximum system effi- ciency of cognitive wireless network as the objective function, achieving the free radio frequency spectrurn＇s dynamic al- location among the cognitive users. Simulations were conducted to compare this algorithm with color sensitive graph co- loring algorithm and traditional binary bacterial foraging optimization algorithm. Results show that the proposed algo- rithm has better performances. It can achieve the maximization of network utility and increase the second user＇s average utility. Compared with the traditional binary bacterial foraging optimization algorithm, it has better optimization ability and faster convergence speed.

关 键 词：认知无线网络 频谱分配 细菌觅食算法 图论着色 量子变异 

分 类 号：TN915.01[电子电信—通信与信息系统]