학술논문

A Cooperative Spectrum Sensing Method Based on a Feature and Clustering Algorithm
Document Type
Conference
Source
2018 Chinese Automation Congress (CAC) Automation Congress (CAC), 2018 Chinese. :1029-1033 Nov, 2018
Subject
Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Sensors
Covariance matrices
Feature extraction
Clustering algorithms
Eigenvalues and eigenfunctions
Matrix decomposition
Training
cooperative spectrum sensing
decomposition and recombination
signal feature extraction
clustering algorithm
Language
Abstract
In order to improve the spectrum sensing performance, we propose a cooperative spectrum sensing method based on a feature and clustering algorithm in the case of a small number of secondary users participating in cooperative spectrum sensing. This method introduces order decomposition and recombination and interval decomposition and recombination based on stochastic matrix, which can increases the secondary users logically. Firstly, the signal matrix collected by the secondary users is split and recombined, and the corresponding covariance matrix are calculated respectively to obtain the corresponding signal features. Based on these features, we construct them as a feature vector. Further, we will use the clustering algorithm to train and perform spectrum sensing based on the trained classifier. In the experimental and results analysis section, the method described in this paper was simulated and the experimental results were further analyzed.