Research On Cooperativ Spectrum Sensing Based On Cyclic Spectrum In Cognitive Radio

With the development of wireless communication technology,the shortage of wireless spectrum resources has become increasingly serious.However,cognitive radio technology can solve the problem of spectrum shortage caused by unbalanced allocation of spectrum resources by making full use of licensed spectrum resources.Cognitive radio allows unauthorized users to access the idle spectrum resources when the channel is not occupied by the authorized users,thus effectively improving the spectrum utilization.Spectrum sensing technology is the key technology of cognitive radio system.The spectrum sensing of target frequency channel can determine whether the unauthorized users can access the channel,so this paper spread of further research based on the spectrum sensing technology.The full paper mainly contains two parts of the research on spectrum sensing technology.Firstly,the single node spectrum sensing based on cyclostationary feature detection algorithm is improved;secondly,the existing fusion rule of multi node cooperative spectrum sensing is improved.The main innovation and research work of this paper is as follows:1.Firstly,this paper introduces the background,research status and key technologies of cognitive radio technology and cognitive radio spectrum sensing,and then describes the basic model of spectrum sensing theory and several common local single node spectrum detection algorithms.Due to cyclostationary feature detection has good detection performance under low SNR,the cyclostationary feature technique is derived and analyzed in detail in this paper.2.Through the analysis of the advantages and disadvantages of current cyclostationary feature detection algorithms,an improved cyclostationary detection algorithm based on SVM is proposed in this paper.Compared with the traditional cyclostationary algorithm,on the one hand,the cyclostationary detection algorithm based on SVM uses high dimensional linear feature space,so it can distinguish cyclostationary signals and noises more accurately.On the other hand,it can collect more feature points,which makes the accuracy of spectrum sensing is improved obviously.MATLAB is used to simulate the algorithm,and the detection performance is analyzed from the aspects of detection probability,false alarm probability,feature point selection and so on.3.In the real spectrum sensing environment,because of the influence of channel fading,shadow effect and distance between receiver and transmitter,the sensing performance of single node spectrum sensing is not ideal.This paper compares the differences between cooperative spectrum sensing and single node spectrum sensing through simulation experiments.Then several current fusion rules are analyzed and compared based on cooperative spectrum sensing.This paper analyzes the problem that the traditional cooperative algorithm does not take into account the trust degree of each user node,and proposes an improved cooperative spectrum sensing algorithm based on the combination of SVM and D-S evidence theory.In this algorithm,a SVM based cyclostationary detection algorithm is applied to the single node spectrum sensing,and D-S evidence theory synthesis rule is introduced.Considering the detection results and reliability factors of each user node,the algorithm solves the disadvantages of the traditional cooperative spectrum sensing algorithm.In this paper,the system model in the implementation process and key technologies were introduced in detail.Through the simulation of the system,the simulation results show that the detection performance of the system has been improved significantly compared with the original algorithm in two aspects:Comparison of detection probability and false alarm probability between improved algorithm and traditional cooperative spectrum sensing algorithm,and Influence of the number of secondary user nodes on system perception performance.