Analysis And Research Of Spectrum Sensing Technology Based On SVM In Cognitive Wireless Network

With the development of society,wireless communication has a greater impact on human life.At the same time,the demand for spectrum resources is also increasing.The traditional wireless spectrum resource allocation mode restricts the flexibility of spectrum utilization and generates spectrum resources.Scarcity issue.In order to meet the development of the times and maximize the need for communication,SS(Spectrum Sensing)technology in the CR(Cognitive Radio)has become a research hotspot in the field of communications,and it can be continuously perceived in wireless environments.Get the state of the spectrum so that more users can use the free spectrum in time to communicate,thus improving the utilization of spectrum resources.This paper aims to determine the spectrum status of the PU(Primary User)in the wireless environment.The presence or absence of the primary user satisfies the discrete classification feature of the SVM(Support Vector Machine)and combines the SVM with the spectrum sensing technology.Research on spectrum sensing technology based on SVM is conducive to the development of CR business.In this paper,based on the analysis of the basic technologies of CR,the research focuses on the spectrum sensing technology in CR.The main content of this article is:1.The theory and working principle of spectrum sensing algorithms such as traditional energy detection(ED)and matched filtering are introduced in detail,and their advantages and disadvantages are analyzed.Based on this,the cooperative spectrum sensing method is described.The method mainly improves the sensitivity of spectrum sensing and low detection reliability.2.By learning the theory of SVM and the characteristics of the kernel function,a spectrum sensing technology based on SVM is implemented.Experimental simulations show that the detection accuracy of spectrum sensing algorithm based on SVM is higher than traditional spectrum sensing algorithm,and its sensing effect is better.3.For the problems existing in single-node spectrum sensing,based on the analysis of the theory of SVM,the cooperative spectrum sensing algorithm based on SVM is studied.The experimental results show that the performance of the cooperative spectrum sensing algorithm based on SVM is better than that of single spectrum sensing.The node frequency spectrum detection algorithm is good;through experiments under the “and”,“or”,and “K rank” data fusion criteria,it is shown that the spectrum sensing algorithm under the “K rank” data processing criterion can significantly enhance the perception effect and improve the accuracy of perception.Degree;The experimental simulation of cooperative spectrum sensing performance based on SVM and non-SVM is performed in the paper.The simulation results show that the cooperative spectrum sensing algorithm based on SVM is better.