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Modelling and performance analysis of energy detector-based spectrum sensing with maximum ratio combining over Nakagami-m/log-normal fading channels

机译:Nakagami-m / log-normal衰落信道上具有最大比率的基于能量检测器的频谱感知建模和性能分析

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摘要

Spectrum sensing (SS) is one of the crucial functions of cognitive radio networks (CRNs). It decides whether the band or sub-band of the spectrum is available or not for secondary users (SUs). Energy detection (ED) is one of the very fundamental approaches of SS to detect whether primary users (PUs) are present or absent. It is mathematically intractable to derive closed-form expressions of composite multipath/shadowing for average probability of detection and average area under the receiver operating characteristic curve. In this paper, we have considered Nakagami-m/log-normal as composite fading with maximum ratio combining (MRC) diversity, and it is approximated by Gaussian-Hermite integration (G-HI). In addition, adaptive threshold or optimised threshold has been incorporated to overcome the problem of spectrum sensing at low signal-to-noise ratio (SNR). To verify the correctness of exact results and obtained analytical expression is collaborated with Monte Carlo simulations.
机译:频谱感测(SS)是认知无线电网络(CRN)的关键功能之一。它决定频谱的频段或子频段是否可用于次要用户(SU)。能量检测(ED)是SS用来检测主要用户(PU)是否存在的最基本方法之一。从数学上讲,很难得出复合多径/阴影的闭合形式的表达式,以求出平均探测概率和接收机工作特性曲线下的平均面积。在本文中,我们将Nakagami-m / log-normal视为具有最大比率合并(MRC)分集的复合衰落,并通过高斯-赫尔米特积分(G-HI)对其进行了近似。另外,已经结合了自适应阈值或优化阈值,以克服在低信噪比(SNR)下进行频谱感测的问题。为了验证精确结果和获得的分析表达式的正确性,与蒙特卡洛模拟进行了协作。

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