Research Of Spectrum Sensing Technology And Implementation Of Dynamic Management Software In Cognitive Radio

Cognitive radio technology can sense the radio spectrum environment,discover and use the idle spectrum within authorized spectrum bands in order to improve the spectrum utilization and relieve the resource demands.It is the hot spot of study in wireless communication filed.Spectrum sensing is one of the key technologies of cognitive radio.The research on this paper is focused on spectrum sensing and implementation of dynamic management software in cognitive radio.First,the research background,definition and key technologies of cognitive radio are introduced,besides,an overview of its development both in china and abroad is given.Secondly,the narrowband spectrum sensing technology based on neural network is studied.Neural network is easy to converge on local optimal solution,and its training convergence speed is slow.In addition,the optimal solution has a deep influence on performance of a spectrum sensing algorithm of neural network.Therefore,neural network is cross-trained by bee colony algorithm to accelerate the training convergence speed and to reduce the mean square error so as to improve the performance of a neural network spectrum sensing algorithm.Using signal energy and spectral correlation as feature parameters,a neural network spectrum sensing algorithm using bee colony optimization is proposed.Simulation results show that the proposed algorithm has better sensing performance compared with the spectrum sensing algorithm based on energy detection,the spectrum sensing algorithm based on cyclostationary,the neural network spectrum sensing algorithm without bee colony cross training and spectrum sensing algorithm based on radial basis function(RBF)neural network.Next,the wideband spectrum sensing technology based on compressed sensing is researched.Sparsity estimation is necessary for wideband spectrum sensing based on compressed sensing.To solve the problems of under-estimation of sparisity at low signal noise ration(SNR)and over-estimation of sparisity at high SNR,a wide-band spectrum sensing algorithm using sparsity estimation based on Gerschgorin theorem is proposed.This algorithm both considers eigenvalue and eigenvector.At first,Gerschgorin theorem is used to separate the signal disk and the noise disk in order to estimate the sparsity.Then,the sparsity is taken as the terminating condition of iteration in orthogonal matching pursuit(OMP)algorithm,and the spectrum support set is obtained by OMP algorithm.Finally,the wideband spectrum sensing is accomplished.The simulation results show that the proposed algorithm takes account of sparsity estimation performances under both low SNR and high SNR,and the spectrum sensing performance is improved.At last,the software design and implementation of a dynamic management system of cognitiveradio is researched.Spectrum management,spectrum sensing and spectrum allocation should be included in cognitive radio dynamic spectrum management system.Therefore,the system is divided into control center module,spectrum sensing server module and spectrum allocation server module.The module interface design and function implementation are based on the Visual C++ 6.0development platform,and the module interaction function is achieved by the design of data transmission frame structure and interactive process.Then,the software of the dynamic management system is realized.Finally,the software is tested in two test scenarios,and the results verify the effectiveness of the system software.