基于特征值的认知无线电多目标仿真分析

Amit Khandelwal, Chhagan Charan
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引用次数: 1

摘要

在认知无线电领域,频谱感知是一个基础性问题。在不相关噪声的情况下,采用不同的方法进行频谱感知。在本文中,我们比较了基于特征值的方法和基于特征值的方法的性能。在基于特征值的方法中,我们利用随机矩阵理论(RMT)找到阈值。Marchenko-Pastur (MP)方法采用标准条件数(SCN)来寻找阈值。这里我们通过使用特征值参数来找到SCN。仿真结果表明,MP律统计提高了感知性能。
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Simulation analysis of MP and eigenvalue based method for cognitive radio
In cognitive radio spectrum sensing is a fundamental problem. Under the case of uncorrelated noise different methods are used for spectrum sensing. In this paper we compare the performance of MP and eigenvalue based methods. In eigenvalue based method we find the threshold using random matrix theory (RMT). Marchenko-Pastur (MP) method use standard condition number (SCN) to find the threshold. Here we find the SCN by using eigenvalue parameters. Simulation shows that MP Law statistics improve the sensing performance.
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