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引用次数: 0
摘要
在存在非高斯噪声的情况下,针对高斯噪声进行优化的传统频谱传感技术可能会出现明显的性能下降。为应对这一挑战,本文采用 Kendall's tau (KT) 作为检测器,在加性拉普拉斯噪声中检测主信号。与依赖原始观测数据基本信息的技术不同,该检测器利用等级来减少脉冲成分的影响,从而对大值异常值具有鲁棒性。首先建立了拉普拉斯噪声下 KT 的期望和方差的解析表达式。并进一步从误报概率和检测概率两个方面进行了性能分析。蒙特卡罗模拟不仅验证了所建立的理论结果的正确性,还证明了 KT 在拉普拉斯噪声下的检测概率优于其他常用方法。
Kendall's Tau Based Spectrum Sensing for Cognitive Radio in the Presence of Laplace Noise
In the presence of non-Gaussian noise, traditional spectrum sensing techniques optimized for Gaussian noise may experience significant performance degradation. To address this challenge, this paper employs Kendall's tau (KT) as a detector to detect the primary signal in additive Laplace noise. Unlike techniques relying on fundamental information from raw observation data, this detector utilizes ranks to reduce the impact of impulsive component, thus being robust against large valued outliers. The analytic expressions concerning the expectation and variance of KT under Laplace noise are firstly established. Performance analyses are further conducted in terms of false alarm probability and detection probability. Monte Carlo simulations not only verified the correctness of the established theoretical results, but also demonstrated the superiority of KT over other commonly used methods in terms of detection probability under Laplace noise.
期刊介绍:
The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing. Papers published in the Letters can be presented within one year of their appearance in signal processing conferences such as ICASSP, GlobalSIP and ICIP, and also in several workshop organized by the Signal Processing Society.