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Immune Parallel Artificial Bee Colony Algorithm For Spectrum Allocation In Cognitive Radio Sensor Networks

机译:认知无线电传感器网络中用于频谱分配的免疫并行人工蜂群算法

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With the rapid development of technology, the continuous progress of communication technology has brought a very serious problem - the shortage of spectrum resources. A large part of the factors that cause the shortage of spectrum resources are related to the original spectrum allocation method. In order to further optimize the benefit of wireless spectrum and network efficiency, this paper proposes an immune parallel artificial bee colony algorithm (IPABCA) to optimize the spectrum allocation efficiency, and uses the classical graph coloring method to calculate the benefit and prove the superiority of group intelligent algorithm in solving the spectrum allocation problem. It can be seen from the simulation results that IPABCA is superior to the original ant colony optimization and particle swarm optimization in terms of total network benefit.
机译:随着技术的飞速发展,通信技术的不断进步带来了非常严重的问题-频谱资源的短缺。造成频谱资源短缺的很大一部分因素与原始频谱分配方法有关。为了进一步优化无线频谱和网络效率的好处,本文提出了一种免疫并行人工蜂群算法(IPABCA)来优化频谱分配效率,并使用经典的图着色方法来计算收益并证明其优越性。群智能算法解决频谱分配问题。从仿真结果可以看出,IPABCA在总体网络收益方面优于原始的蚁群优化和粒子群优化。

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