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Signal detection for spectrum sensing with uncertain arrivals of traffics

机译:流量到达不明时频谱检测的信号检测

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摘要

Due to random arrivals of primary user signals, their timing misalignment issue should be considered for spectrum sensing in cognitive radio (CR) systems, such as CR based femtocell networks. To deal with this issue in the literature, two approaches were recommended, including Bayesian and generalized likelihood ratio test (GLRT) detectors. However, Bayesian test requires the perfect knowledge of the distribution of unknown parameters. Therefore, it is considered to be impractical due to its implementation complexity. To design a low complexity energy detector (ED), this work proposes an ED scheme based on GLRT algorithm. As a result, maximum-likelihood (ML) estimation for the timing misalignment is devised, and the performance of the proposed scheme is analyzed. The results show that the proposed GLRT detector features a low complexity and satisfactory performance.
机译:由于主要用户信号的随机到达,对于诸如基于CR的毫微微小区网络的认知无线电(CR)系统中的频谱感测,应考虑其时序未对准问题。为了解决文献中的这个问题,推荐了两种方法,包括贝叶斯和广义似然比测试(GLRT)检测器。但是,贝叶斯测试需要对未知参数的分布有全面的了解。因此,由于其实现复杂性而被认为是不切实际的。为了设计低复杂度的能量检测器(ED),本文提出了一种基于GLRT算法的ED方案。结果,设计了时序未对准的最大似然(ML)估计,并分析了所提出方案的性能。结果表明,所提出的GLRT检测器具有低复杂度和令人满意的性能。

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