Improved Blind Spectrum Sensing by Covariance Matrix Cholesky Decomposition and RBF-SVM Decision Classification at Low SNRs

Improved Blind Spectrum Sensing by Covariance Matrix Cholesky Decomposition and RBF-SVM Decision Classification at Low SNRs

An improved blind spectrum sensing scheme is established by the covariance matrix Cholesky decomposition and radial basis function (RBF)-support vector machine (SVM) decision classification at low signal-to-noise ratios (SNRs). Under strong background noises, the proposed scheme improves the recogni...

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Bibliographic Details
Main Authors: Jianrong Bao, Jianyuan Nie, Chao Liu, Bin Jiang, Fang Zhu, Jianhai He
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Blind spectrum sensing
Cholesky decomposition
RBF-SVM
covariance matrix
decision classification
Online Access:https://ieeexplore.ieee.org/document/8764555/

Internet

https://ieeexplore.ieee.org/document/8764555/

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