Cooperative Spectrum Sensing Strategy Based On Second-order Statistics In Heterogeneous Wireless Networks

Cognitive radio technology provides the best solution to solve the spectrum tense and the raising of utilization ratio of spectrum,while the spectrum sensing technology is the foundation of cognitive radio technology,which performance is directly related with the performance of the system,so it is of great significance to do research on this subject.Spectrum sensing in a real environment is vulnerable to noise power,low SNR condition such as volatility etc.And in broadband spectrum perception,due to the increased communication bandwidth,the too high rate of ADC sampling in the process of problem,spectrum sensing needs more and more high requirement of sensing device.In order to solve the spectrum sensing problem of uncertain noise variance,low signal-to-noise ratio,and broadband communication under the condition of different spectrum sensing,in this paper,the perception algorithm and cognitive strategies are studied,the main work is as follows:Firstly,for cognitive radio technologies,it is important not to accurately reconstruct the signal itself,but to accurately detect the location of both free and occupied frequency bands.According to this idea,lossy compression can be used to accurately reconstruct the signal second-order statistics instead of reconstructing the signal itself to determine the spectrum usage.Therefore,it is not necessary to assume that the signal is sparse in the frequency band and only blindly reconstruct the signal power Value,reducing the computational complexity.In addition,the size of the covariance matrix used to replace the original sample is not increased with the number of samples as the structure of the signal second-order statistics has the features of Toplérite and Hermite.Is to maintain a certain dimension to meet the computational convenience and accuracy of the likelihood function,and to ensure that the non-singularity of the correction matrix,which can greatly reduce the computational complexity and reduce the hardware requirements;Secondly,A cooperative spectrum sensing algorithm based on power value detection is proposed to provide a solution for the sparse spectrum of current heterogeneous.The algorithm is based on the prerequisite that there is no correlation between the various types of signals in the authorized frequency band.Firstly,we select several users with the best instantaneous channel conditions as the perceptual users.Then these perceptual users are utilized to detect the Occupancy of all kinds of signals in the authorized frequency band.During the process of determining the use of certain types of signals in the authorized frequency band,the algorithm can be used to remove the influence of other signals,for the sake of the accuracy and reliability of the test without increasing complexity.The theoretical analysis and simulation results prove that this algorithm indeed realizes this goal--the validity and reliability of the test.