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作 者:孙汉卿 刘征 王桂芝 连卫民 Sun Hanqing;Liu Zheng;Wang Guizhi;Lian Weimin(College of Information Engineering,Henan University of Animal Husbandry and Economu,Zhengzhou 450044,Henan,China)
机构地区:[1]河南牧业经济学院信息工程学院,河南郑州450044
出 处:《计算机应用与软件》2020年第12期260-265,321,共7页Computer Applications and Software
基 金:河南省科技发展计划项目(182102210599);河南牧业经济学院科研创新团队项目(2018KYTD19)。
摘 要:传统基于蚁群算法的认知无线电频谱分配方案未考虑信息素分配时间因素,导致信道使用效率低,对此给出一种基于多态蚁群优化算法的认知无线电频谱分配方案。计算基于蚁群算法的转移概率,为蚁群算法中蚂蚁的下一步行动提供依据;在信息素分配过程中引入一个时间因子,使信息素的分配与蚂蚁到达节点的时间有关,生成新的信息素分配方法;对所有认知用户的信息素进行排序,并将信道分配给信息素最大的认知用户。仿真实验结果表明:该算法可以保证信息素分配的公平性且可以提高信道利用率,与AOC算法、QGA算法和CSGC算法相比,可以显著提高系统的网络效益、公平性、收敛速度和吞吐量。The traditional cognitive radio spectrum allocation scheme based on ant colony algorithm does not take into account the time factor of pheromone allocation,which leads to the low efficiency of channel utilization.Therefore,we propose a cognitive radio spectrum allocation scheme based on polymorphic ant colony optimization algorithm.It calculated the transition probability based on ant colony algorithm,which provided the bases for the next action of ants in the ant colony algorithm.A time factor was introduced in the process of pheromone allocation,which made the allocation of pheromone related to the time when the ants arrived at the node,and generated a new pheromone allocation method.The pheromones of all cognitive users were sorted,and the channel was allocated to the cognitive users with the largest pheromone.The simulation results show that the proposed algorithm can guarantee the fairness of pheromone allocation and improve the channel utilization.Compared with AOC,QGA and CSGC,it can significantly improve the network efficiency,fairness,convergence speed and throughput of the system.
关 键 词:多态蚁群算法 认知无线电 频谱分配 时间效率 转移概率
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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