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Optimization of probability of false alarm and probability of detection in cognitive radio networks using GA

机译:基于遗传算法的认知无线电网络中虚警概率和检测概率的优化

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摘要

In this paper, we optimize probability of detection and probability of false alarm in cognitive radio network to minimize probability of error of a particular SU in a centralized cognitive radio network using Genetic algorithm (GA). Our objective is to minimize probability of error and find out optimum values of probability of occupancy detection or probability of detection and probability of false alarm. We use Genetic Algorithm to solve this optimization problem. The result is compared with Differential Evolution algorithm and it is evident from the comparison that DE finds better solution and takes much lesser number of evaluations to find optimum solution.
机译:在本文中,我们使用遗传算法(GA)优化了认知无线电网络中的检测概率和虚警概率,以最小化集中式认知无线电网络中特定SU的错误概率。我们的目标是最大程度地减少错误发生的可能性,并找出占用检测或检测的概率与虚警的概率的最佳值。我们使用遗传算法来解决此优化问题。将结果与差分进化算法进行比较,从比较中可以明显看出,DE可以找到更好的解决方案,并且需要更少的评估次数来找到最优解。

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