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首页> 外文期刊>Wireless personal communications: An Internaional Journal >Spectrum Sensing in Cognitive Radio Using Actor-Critic Neural Network with Krill Herd-Whale Optimization Algorithm
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Spectrum Sensing in Cognitive Radio Using Actor-Critic Neural Network with Krill Herd-Whale Optimization Algorithm

机译：磷灰虫鲸鲸优化算法使用演员 - 评论家神经网络的认知无线电频谱感应

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Spectrum sensing is the active research area in the Cognitive radio networks that initiates the effective data sharing between the licensed and the unlicensed users of Cognitive Network. Maximizing the detection probability for a provided false alarm rate is a hectic challenge of most of the spectral sensing methods. The paper proposes a spectral sensing method, termed as Krill-Herd Whale optimization-based actor critic neural network. The unoccupied spectrum is optimally determined using the proposed method that allocates the free spectrum bands to the primary users instantly such that the delay is minimized due to the effective functioning of the fusion center. For the effective sensing, the Eigen-value-based cooperative sensing is activated in the cognitive radio. The analysis of the proposed method is progressed based on the performance metrics, such as false alarm probability and detection probability. The proposed spectral sensing method outperforms the existing methods that yield a maximum probability of detection and minimum probability of false alarm at a rate of 0.9805 and of 0.009.
机译：频谱感测是认知无线电网络中的主动研究区域，它在许可和未经许可的认知网络之间发起有效数据共享。为提供的误报率最大化检测概率是大多数光谱传感方法的繁忙挑战。本文提出了一种谱检测方法，称为基于KRILL-HELD鲸鲸优化的演员批评神经网络。使用该方法最佳地确定未占用的频谱，该方法立即将自由频谱带分配给主用户，使得由于融合中心的有效功能，延迟最小化。为了有效感测，基于特征值的协作感测在认知无线电中激活。基于性能指标进行提出的方法的分析，例如误报概率和检测概率。所提出的光谱传感方法优于现有的方法，其以0.9805的速率和0.009的速率产生最大检测和最小概率的最大概率。

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