电讯技术2023，Vol.63Issue(12)：1911-1917,7.DOI:10.20079/j.issn.1001-893x.220816001
一种基于特征值和级联聚类的协作频谱感知方法
A Cooperative Spectrum Sensing Method Based on Eigenvalue and Cascade Clustering
摘要
Abstract
In order to improve the performance of spectrum sensing in low signal to noise ratio(SNR),a cooperative spectrum sensing method based on eigenvalue and cascade clustering is proposed by using Fuzzy C-means(FCM)and Gaussian Mixture Model(GMM).The feature vectors are constructed by extracting the eigenvalues from the covariance matrix of the received signals,and the classification model of whether the channel is available is obtained by performing clustering in three-dimensional space.This process does not need to obtain the prior information of the primary user(PU)signal and the noise power,which avoids the complex threshold calculation.FCM clustering is used to optimize the initial parameters of GMM clustering,which effectively solves the problem that GMM is prone to fall into local minimum in low SNR.Simulation results show that the proposed method both reduces the convergence time of GMM and improves the accuracy of model classification.Compared with other mainstream methods,it can effectively improve the spectrum sensing performance.关键词
认知无线电/协作频谱感知/高斯混合模型/级联聚类Key words
cognitive radio/cooperative spectrum sensing/Gaussian mixture model/cascade clustering分类
信息技术与安全科学引用本文复制引用
吴城坤,王全全,宛汀..一种基于特征值和级联聚类的协作频谱感知方法[J].电讯技术,2023,63(12):1911-1917,7.基金项目
国家自然科学基金资助项目(62071245) （62071245）
