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arXiv 0905.0024cs.ITmath.IT
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认知无线电系统中循环频域噪声与特征检测的理论分析

Theoretical Analysis of Cyclic Frequency Domain Noise and Feature Detection for Cognitive Radio Systems

Gan Xiaoying, Shan Da, Zhou Yuan, Zhang Wei, Qian Liang

摘要:

在认知无线电系统中,循环平稳特征检测在频谱感知中起着重要的作用,特别是在低信噪比的情况下。为了在一定的噪声水平和预设的漏检概率Pf下配置检测阈值,推导观测变量的理论分布是很重要的。本文研究了循环频域中的噪声分布,发现广义极值(GEV)分布是一种精确的匹配。采用极大似然估计方法对GEV参数进行估计。蒙特卡洛模拟结果表明,模拟ROC曲线与理论ROC曲线吻合较好,证明了理论分布模型的有效性。

英文摘要:

In cognitive radio systems, cyclostationary feature detection plays an important role in spectrum sensing, especially in low SNR cases. To configure the detection threshold under a certain noise level and a pre-set miss detection probability Pf, it's important to derive the theoretical distribution of the observation variable. In this paper, noise distribution in cyclic frequency domain has been studied and Generalized Extreme Value (GEV) distribution is found to be a precise match. Maximum likelihood estimation is applied to estimate the parameters of GEV. Monte Carlo simulation has been carried out to show that the simulated ROC curve is coincided with the theoretical ROC curve, which proves the efficiency of the theoretical distribution model.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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