Multiantenna-Assisted Spectrum Sensing for Cognitive Radio
Multiantenna-Assisted Spectrum Sensing for Cognitive Radio
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DOI：
10.1109/tvt.2009.2037912
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发表时间：
2010-05
影响因子：
6.8
通讯作者：
Pu (Perry) Wang;Jun Fang;Ning Han;Hongbin Li
中科院分区：
文献类型：
--
作者：
Pu (Perry) Wang;Jun Fang;Ning Han;Hongbin Li
在本文中，我们考虑的问题，在认知无线电网络中，通过采用多个天线在认知接收机的主用户检测。在车辆应用中，认知无线电通常会经过具有不同主用户密度的区域。因此，检测速度是关键，因此，基于少量样本的检测对于车辆应用特别有利。假设没有先验知识的主用户的信令方案，主用户和认知用户之间的信道，以及在认知用户看到的噪声的方差，广义似然比测试（GLRT）开发检测主用户的存在/不存在。渐近性能分析所提出的GLRT。在噪声方差未知或不准确已知的情况下，将该方法与能量检测器（艾德）和几种基于特征值的方法进行了性能比较.我们的研究结果表明，建议GLRT表现出更好的性能比其他现有的技术，特别是当样本的数量是小的，这是特别关键的车辆应用。
In this paper, we consider the problem of detecting a primary user in a cognitive radio network by employing multiple antennas at the cognitive receiver. In vehicular applications, cognitive radios typically transit regions with differing densities of primary users. Therefore, speed of detection is key, and so, detection based on a small number of samples is particularly advantageous for vehicular applications. Assuming no prior knowledge of the primary user's signaling scheme, the channels between the primary user and the cognitive user, and the variance of the noise seen at the cognitive user, a generalized likelihood ratio test (GLRT) is developed to detect the presence/absence of the primary user. Asymptotic performance analysis for the proposed GLRT is also presented. A performance comparison between the proposed GLRT and other existing methods, such as the energy detector (ED) and several eigenvalue-based methods under the condition of unknown or inaccurately known noise variance, is provided. Our results show that the proposed GLRT exhibits better performance than other existing techniques, particularly when the number of samples is small, which is particularly critical in vehicular applications.