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Hard Decision Fusion based Cooperative Spectrum Sensing in Cognitive Radio System

机译:认知无线电系统中基于硬决策融合的协作频谱感知

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Cooperative spectrum sensing was proposed to combat fading, noise uncertainty, shadowing, and even hidden node problem due to primary users (PUs) activity that is not spatially localized. It improves the probability of detection by collaborating to detect PUs signal in cognitive radio (CR) system as well. This paper studies cooperative spectrum sensing and signal detection in CR system by implementing hard decision combining in data fusion centre. Through computer simulation, we evaluate the performances of cooperative spectrum sensing and signal detection by employing OR and AND rules as decision combining. Energy detector is used to observe the presence of primary user (PU) signal. Those results are compared to non-cooperative signal detection for evaluation. They show that cooperative technique has better performance than non-cooperative. Moreover, signal to noise ratio (SNR) with greater than or equal 10 dB and 15 collaborated users in CR system has optimal value for probability of detection.
机译:有人提出了协作频谱感测来解决由于主要用户(PU)活动未在空间上本地化而导致的衰落,噪声不确定性,阴影甚至隐藏节点问题。它也通过在认知无线电(CR)系统中协作检测PU信号来提高检测的可能性。本文通过在数据融合中心实施硬决策组合研究CR系统中的协作频谱感知和信号检测。通过计算机仿真,我们采用OR和AND规则作为决策组合,评估了协作频谱感知和信号检测的性能。能量检测器用于观察主要用户(PU)信号的存在。将这些结果与非合作信号检测进行比较以进行评估。他们表明合作技术比非合作技术具有更好的性能。此外,CR系统中15个协作用户的大于或等于10 dB的信噪比(SNR)具有最佳的检测概率值。

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