遗传算法在认知无线电网络频谱分配中的有效性研究

Abdelbaset S. Hamza, Mona M. Elghoneimy
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引用次数: 13

摘要

在本文中,进行了广泛的研究,以了解在遗传算法(GA)中使用的各种参数的影响,以解决认知无线电网络中的频谱分配问题。利用Mean-Reward和Max-Proportional-Fair两个利用函数来评价遗传算法在不同参数值下的性能。大量的仿真表明,与文献中使用的遗传算法相比,遗传算法的参数可以微调,分别在速度和误差方面提高90%和62%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the effectiveness of using Genetic Algorithm for spectrum allocation in cognitive radio networks
In this paper, an extensive study is performed to understand the effect of the various parameters used in Genetic Algorithms (GA) to solve the spectrum allocation problem in cognitive radio networks. Two utilization functions, namely, Mean-Reward, and Max-Proportional-Fair, are used to evaluate the performance of the GA under different parameters values. Extensive simulation shows that, the parameters of the GA can be fine-tuned to achieve up to 90% and 62% improvements in speed and error, respectively, as compared to the GA used in the literature.
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