频谱检测中基于FCM的自适应门限选择机制

发布时间：2018-05-05 16:20

本文选题：频谱检测 + 能量感知　；参考：《系统工程与电子技术》2015年12期

【摘要】：在认知无线电中,能量检测法是次用户实现频谱检测的重要方法之一。其中,检测参数的设置尤为重要。然而,当无线网络环境改变时,一些重要检测参数(如检测器门限)将会随之改变,因而及时准确地获取检测参数就显得十分必要。本文首先在理想高斯白噪声信道条件下推导了能量检测的最佳门限表达式。为了在变化的网络环境中快速自适应地获得最佳门限并降低检错率,提出了一种基于模糊C均值(fuzzy C-means,FCM)的自适应门限选择机制。该机制只需根据接收到的能量样本的相似性和差异性进行聚类,选取隶属度值差异最小的能量样本作为最佳门限值,而无需信噪比、初始门限等先验信息,因此在能量检测中具有更强的自适应性。Matlab仿真结果证明,新机制下获取的最佳门限与本文中推导的高斯白噪声信道下的最佳检测器门限相比,具有很好的拟合度。
[Abstract]:In cognitive radio, energy detection is one of the important methods of spectrum detection for secondary users. Among them, the setting of detection parameters is particularly important. However, when the wireless network environment changes, some important detection parameters (such as detector threshold) will change, so it is necessary to obtain the detection parameters accurately and timely. In this paper, the optimal threshold expression for energy detection is first derived under the condition of ideal Gao Si white noise channel. In order to obtain the best threshold and reduce the error detection rate quickly and adaptively in the changing network environment, an adaptive threshold selection mechanism based on fuzzy C-means fuzzy C-means (FCM) is proposed. The mechanism only needs to cluster according to the similarity and difference of the received energy samples and select the energy samples with the smallest difference of membership value as the best threshold value without prior information such as signal-to-noise ratio and initial threshold. The simulation results of Matlab show that the optimal threshold obtained under the new mechanism is better than the optimal detector threshold under Gao Si white noise channel derived in this paper.
【作者单位】：南京邮电大学通信与信息工程学院;南京邮电大学教育部宽带无线通信与传感网技术重点实验室;
【基金】：国家自然科学基金(61471200) 国家高技术研究发展计划(863计划)(2009AA01Z241) 江苏省自然科学基金青年基金项目(BK20140885) 江苏省博士后科研资助计划(1401045C) 南京邮电大学科研基金项目(NY214034)资助课题
【分类号】：TN925

【相似文献】