Research On Spectrum Sensing Technology In Cognitive Radio

With the advancement of society and the rapid development of radio communication technology,the demand for communication services is becoming larger and larger.However,spectrum resources are a very limited and valuable resource.Therefore,it is very important to achieve reasonable management and allocation of spectrum resources and improve the utilization of spectrum resources.In this paper,spectrum sensing technology is used to find spectrum holes,that is,unused spectrum,and these detected spectrum holes are reasonably allocated and used to solve the problem of low spectrum utilization and spectrum shortage.In order to improve the ability to detect spectral holes to improve the utilization of spectrum resources,mainly does the following work:When double-threshold energy detection is adopted for both layers of perception,if the detection statistics fall within the two decision thresholds twice,it is impossible to accurately determine whether the main user has problems.The two-layer perception algorithm based on double threshold energy and cyclostationarity is studied.In the first layer of perception,when the signal power is high,the signal statistics fall on both sides of the two decision thresholds,so the second layer of perception is unnecessary.When the signal power is low,the signal statistics fall within the two decision thresholds,and a second layer of perception is needed to further judge the spectrum situation.The algorithm takes both computation and detection into account.The simulation results show that the detection performance of the two-layer sensing algorithm is better than that of the two-threshold energy detection and the cyclostationary characteristic detection.At the same time,for cognitive users who use the two-layer perception algorithm based on double-threshold energy and cyclostationarity,if their computing power is low and the number of samples is not high,their detection performance will be poor.The multi-user cooperative spectrum sensing algorithm based on the weighted sampling number is studied.This algorithm improves the detection performance of the cooperative sensing system by increasing the weighted weight of the cognitive users with high sampling number to participate in the decision and increasing the influence of the users with high sampling number on the final decision.Simulation results show that the detection performance of weighted fusion algorithm based on sample number is better than that of traditional AND criterion fusion algorithm and K criterion fusion algorithm.Aiming at the collaborative perception network of cognitive users with low SNR and malicious cognitive users,this paper studies the fusion algorithm based on the correlation weighting between cognitive users.The correlation between cognitive users is calculated to find those unreliable cognitive users.The algorithm can adjust the influence of the local judgment result of cognitive users on the final judgment result by setting the weighted weight,and finally improve the detection performance of the cooperative perception network.The simulation results show that the algorithm can achieve the above functions well and improve the detection performance of the system.