非高斯噪声中基于分数低阶统计量的频谱感知技术研究

项目名称： 非高斯噪声中基于分数低阶统计量的频谱感知技术研究

项目编号： No.61501223

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 无线电电子学、电信技术

项目作者： 朱晓梅

作者单位： 南京工业大学

项目金额： 19万元

中文摘要： 在非高斯噪声背景下，传统的基于二阶统计量、最优检测器及次优化检测器的频谱感知方法性能将出现退化或失效。本课题针对此问题，对非高斯噪声背景下的频谱感知存在的问题进行深入的研究。前期研究工作表明，非高斯噪声的概率密度函数重拖尾现象是导致基于高斯噪声假设的感知方法性能退化的关键因素。本课题拟采用数值仿真与实验研究相结合的方法，建立以α稳定分布、广义高斯分布为背景噪声模型的频谱感知系统，对分数低阶统计量理论做深入的研究，利用分数低阶矩（FLOM）、分数低阶协方差(FLOC)等非线性处理方法，通过降低噪声尖峰来减弱拖尾现象，从而有效提高检测概率，并结合实际感知信道、融合信道存在瑞利衰落或Nakagami衰落的情况，探讨优化算法进一步提高多用户协作感知性能，最终实现非高斯噪声环境中最大程度地动态共享空白频谱的同时又不会对主用户的通信带来干扰，为认知无线电网络走向实际应用提供理论与技术支持。

中文关键词： 协作频谱感知；非高斯噪声；；分数低阶统计量

英文摘要： The traditional spectrum sensing methods based on second order statistics are in general not applicable to detecting the primary user in non-Gaussian noises with unknown parameters. This paper presents an FLOM (fractional lower order moment)-based spectrum sensing scheme for the background noise with α-stable distribution. The new method does not require any a priori knowledge of the primary user. By using the central limit theorem, the relationship between the sensing threshold and the probability of false alarm is disclosed. The detection performance of the proposed method versus the generalized signal-to-noise ratio, dispersion α and the number of cooperative users is studied by Monte Carlo simulations with comparison to the traditional method. Simulation results show that the proposed method has a much better performance than the energy detection method does in α-stable distributed noise environment. It is also shown that using multi-user cooperation can provide a significantly higher probability of detection than that of the single user version.

英文关键词： Cooperative sepctrum sensing;Non-Gassian noise;fractional lower order statistics