GLRT-Based Spectrum Sensing for Cognitive Radio
GLRT-Based Spectrum Sensing for Cognitive Radio
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DOI：
10.1109/glocom.2008.ecp.842
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发表时间：
2008-12
期刊：
影响因子：
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通讯作者：
Teng Joon Lim;Rui Zhang;Ying-Chang Liang;Yonghong Zeng
中科院分区：
文献类型：
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作者：
Teng Joon Lim;Rui Zhang;Ying-Chang Liang;Yonghong Zeng
在本文中，我们提出了几种频谱感知方法设计使用广义似然比检验（GLRT）的范例，在认知无线电网络中的应用。所提出的技术利用接收信号向量的样本协方差矩阵的特征值，利用以下事实：在实践中，认知无线电环境中的主信号将占据维度严格小于观测空间的维度的子空间，或者具有非白色的频谱。我们表明，通过对边信息的可用性，如噪声方差和信号空间维度的各种假设，几个可行的算法的结果，所有优于标准的能量检测器。
In this paper, we propose several spectrum sensing methods designed using the generalized likelihood ratio test (GLRT) paradigm, for application in a cognitive radio network. The proposed techniques utilize the eigenvalues of the sample covariance matrix of the received signal vector, taking advantage of the fact that in practice, the primary signal in a cognitive radio environment will either occupy a subspace of dimension strictly smaller than the dimension of the observation space, or have a spectrum that is non-white. We show that by making various assumptions on the availability of side information such as noise variance and signal space dimension, several feasible algorithms result which all outperform the standard energy detector.