Research On Spectrum Sensing Based On Covariance Matrix And Communication System In Cognitive Radio

In recent years,as the wireless communication technology and its related services enter a stage of rapid development,the limited spectrum resources become increasingly scarce and tense,and their lower spectrum utilization rate has become a constraint to the development of wireless communications bottleneck.To support the communication of various wireless services and devices in a non-disruptive environment,the spectrum management institution has introduced a Fixed-Spectrum Access Policy(FSA)that allocates fixed bandwidth to designated users or users.Through this provision,only authorized users or devices have access to the allocated frequency band,and unauthorized users are not allowed to use,regardless of whether the current authorized user is using the licensed frequency band.Over the past decade or so,with the continuous development and proliferation of wireless services,most of the available spectrum has been completely allocated and the problem of spectrum scarcity has become more and more serious.On the other hand,recent studies show that the licensed spectrum has not been fully utilized in many cases in practice.In order to maintain the sustainable development of wireless communication services,new solutions should be developed to improve the utilization efficiency of the radio frequency spectrum.Cognitive radio is one of the key technologies to solve these problems.Spectrum sensing in cognitive radio is the most basic functional module and is also the cornerstone of the entire cognitive radio technology.Although the research results of spectrum sensing module are continuously abundant in recent years,under the severe environment,such as the low signal-to-noise ratio and the multipath effect caused by complex scene perception,the existing algorithms still have long sensing period,Low perceived accuracy.Therefore,the research on spectrum sensing still needs further study.The thesis regards cognitive radio as its research direction and mainly studies the spectrum sensing technology in the key technologies of cognitive radio.The main work of this dissertation is as follows:1,Two types of single-point-spectrum and cooperative spectrum sensing technologies in cognitive radio are analyzed,and the derivation process of classical spectrum sensing technology based on transmitter detection is given.The criteria of hard and soft decision in collaborative detection are introduced,and several commonly used fusion criteria are given.2,Two kinds of algorithms in covariance matrix-based perceptual algorithm are analyzed,and the theoretical derivation of four classical covariance matrices is given.At the same time,a new covariance matrix-based perceptual algorithm was found,and the derivation of statistical threshold based on this algorithm was given.3,Based on matlab communication simulation platform,the possibility of adding adaptive function on the perceptual side and its adaptive modulation criteria are analyzed.The classical energy spectrum sensing algorithm is simulated based on matlab communication simulation platform.At the same time,the proposed algorithm is simulated by matlab communication simulation platform,and the performance of the algorithm under different orders of modulation and different signal-to-noise ratios is compared with several classical perceptual algorithms.