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Cognitive Radio Decision Engine Based on Priori Knowledge

机译:基于先验知识的认知无线电决策引擎

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摘要

Given a dynamic wireless spectrum environment, to find the optimal decision in a huge solution space is primary feature of cognitive radio decision engine for wireless communication systems. Current researches mainly focus on evolutionary algorithm. However, the current researches completely transform the problem into mathematical problems and ignore the particularity of the problem itself. This article uses the immune theory, leading the priori knowledge into evolutionary algorithm, to guide the evolutionary process. By comparing with the simple genetic algorithm (SGA), the experiments prove method feasible and effective. At last, this article noted that the method can greatly increase the efficiency of the most current cognitive radio decision engines using evolutionary algorithm.
机译:在给定动态无线频谱环境的情况下,在巨大的解决方案空间中找到最佳决策是用于无线通信系统的认知无线电决策引擎的主要特征。目前的研究主要集中在进化算法上。但是,目前的研究将问题完全转化为数学问题,而忽略了问题本身的特殊性。本文使用免疫理论,将先验知识引入进化算法,以指导进化过程。通过与简单遗传算法(SGA)的比较,实验证明了该方法的可行性和有效性。最后,本文指出,该方法可以大大提高使用进化算法的最新认知无线电决策引擎的效率。

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