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Moment-based Spectrum Sensing Under Generalized Noise Channels
arXiv - CS - Information Theory Pub Date : 2020-09-09 , DOI: arxiv-2009.06386
Nikolaos I. Miridakis, Theodoros A. Tsiftsis and Guanghua Yang

A new spectrum sensing detector is proposed and analytically studied, when it operates under generalized noise channels. Particularly, the McLeish distribution is used to model the underlying noise, which is suitable for both non-Gaussian (impulsive) as well as classical Gaussian noise modeling. The introduced detector adopts a moment-based approach, whereas it is not required to know the transmit signal and channel fading statistics (i.e., blind detection). Important performance metrics are presented in closed forms, such as the false-alarm probability, detection probability and decision threshold. Analytical and simulation results are cross-compared validating the accuracy of the proposed approach. Finally, it is demonstrated that the proposed approach outperforms the conventional energy detector in the practical case of noise uncertainty, yet introducing a comparable computational complexity.

中文翻译:

广义噪声信道下基于矩的频谱传感

当它在广义噪声信道下工作时,提出并分析研究了一种新的频谱感测检测器。特别是,McLeish 分布用于对底层噪声进行建模,它适用于非高斯(脉冲)和经典高斯噪声建模。引入的检测器采用基于矩的方法,而不需要知道发射信号和信道衰落统计(即盲检测)。重要的性能指标以封闭形式呈现,例如误报概率、检测概率和决策阈值。分析和模拟结果进行了交叉比较,验证了所提出方法的准确性。最后,证明了所提出的方法在噪声不确定性的实际情况下优于传统的能量检测器,
更新日期:2020-09-15
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