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ADAPTIVE EIGENVALUE-BASED SPECTRUM SENSING FOR MULTI-ANTENNA COGNITIVE RADIO SYSTEMS

机译:基于自适应的特征值基于基于特征值的多天线认知无线电系统的频谱感测

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In this paper adaptive Eigenvalue-Based Spectrum Sensing (EBSS) techniques are proposed for multi-antenna cognitive receivers. In cases where fading channels are involved, and hence real-time processing is required, the adaptive techniques offer lower complexity and exhibit improved performance as compared to the corresponding batch EBSS techniques. At first, novel adaptive EBSS techniques are developed for the Maximum Eigenvalue Detector (MED), the Maximum-Minimum Eigenvalue Detector (MMED), and the Generalized Likelihood Ratio Test (GLRT) schemes, respectively, based on well-studied subspace tracking methods. Moreover, close approximations for the distribution functions of the adaptive test statistics of the MED, MMED and GLRT schemes are derived in order to compute the decision thresholds for a given probability of false alarm. The performance of the adaptive EBSS methods is verified via indicative simulations.
机译:在本文中,提出了基于自适应的特征值的频谱感测(EBS)技术,用于多天线认知接收器。在涉及衰落通道的情况下,因此需要实时处理,与相应的批量EBS技术相比,自适应技术提供更低的复杂性并表现出改善的性能。首先,基于所学习的子空间跟踪方法,开发了用于最大特征值检测器(MED),最大 - 最小特征值检测器(MMED)和广义似然比测试(GLRT)方案的最大特征值探测器(MUD)的新型自适应EBS技术。此外,导出了MED,MMED和GLRT方案的自适应测试统计分布函数的近似近似,以计算给定误报概率的判定阈值。通过指示模拟验证自适应EBSS方法的性能。

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