Spectrum Sensing Using Weighted Covariance Matrix in Rayleigh Fading Channels
Spectrum Sensing Using Weighted Covariance Matrix in Rayleigh Fading Channels
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在瑞利衰落通道中使用加权协方差矩阵进行频谱感知
DOI：
10.1109/tvt.2014.2379924
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发表时间：
2015-11-01
影响因子：
6.8
通讯作者：
Huang, Defeng
中科院分区：
文献类型：
--
作者：
Jin, Ming;Guo, Qinghua;Huang, Defeng
基于协方差的检测是一种利用主信号的空间和/或时间相关性的低复杂度盲频谱感知方案。然而，随着信号相关性的降低，其性能严重下降。在这项工作中，提出了一个加权的协方差检测器，通过引入数据辅助的权重的协方差矩阵。分析了低信噪比下的虚警概率、判决门限和检测概率，并基于中心极限定理导出了它们的近似解析表达式。通过仿真验证了分析。仿真多天线信号和现场测量数字电视信号的实验表明，所提出的加权检测可以显着优于原来的基于协方差的检测。
Covariance-based detection is a low-complexity blind spectrum sensing scheme that exploits spatial and/or temporal correlations of primary signals. However, its performance severely degrades with the decrease of signal correlations. In this work, a weighted-covariance-based detector is proposed by introducing data-aided weights to the covariance matrix. The false alarm probability, decision threshold, and detection probability are analyzed in the low signal-to-noise ratio (SNR) regime, and their approximate analytical expressions are derived based on the central limit theorem. The analyses are verified through simulations. Experiments with simulated multiple-antenna signals and field measurement digital television signals show that the proposed weighted detection can significantly outperform the original covariance-based detection.