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首页> 外文期刊>International Journal of Applied Engineering Research >Optimization of Sensing Time in Energy Detector Based Sensing of Cognitive Radio Network
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Optimization of Sensing Time in Energy Detector Based Sensing of Cognitive Radio Network

机译:基于认知无线电感知的能量检测器中的感知时间优化

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摘要

In cognitive radio network, spectrum sensing methods detect the existence of primary users to utilize spectrum holes for secondary users. When it is found that there are no busy primary users then secondary users are allowed to transmit through the spectrum. During the transmission process of secondary users, there may be collision between secondary users. This leads to decrease in the throughput of the samples of secondary users. In this paper, a mathematical expression for collision between samples of secondary users is derived using Poisson distribution. It is found that by optimizing sensing time, the probability of collision can be set below a predefined threshold as well as the throughput of secondary users can be increased under given probability of detection and under different signal-to-noise ratio conditions of the transmitted channels in the cognitive radio network. Optimization of sensing time is done using Human behavior based particle swarm optimization (HBPSO). By doing this, the probability of collision between samples of secondary users is minimized and a high value of system throughput (~90%) is obtained.
机译:在认知无线电网络中,频谱感测方法检测主要用户的存在,以利用次要用户的频谱漏洞。当发现没有繁忙的主要用户时,则允许次要用户通过频谱进行传输。在次要用户的传输过程中,次要用户之间可能会发生冲突。这导致二级用户的样本的吞吐量降低。在本文中,使用泊松分布推导了二级用户样本之间冲突的数学表达式。已经发现,通过优化感测时间,可以将冲突概率设置为低于预定阈值,并且可以在给定的检测概率下以及在所发射信道的不同信噪比条件下提高次要用户的吞吐量。在认知无线电网络中。使用基于人类行为的粒子群优化(HBPSO)来完成感测时间的优化。通过这样做,最小化了二级用户样本之间发生冲突的可能性,并获得了很高的系统吞吐量(〜90%)。

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