Research On Spectrum Detection Algorithm Of Satellite Cognitive Network

As communication technology is full of influence in all walks of life,the required spectrum resources have not been agreed on in ter ms of supply.Therefore,in some aspects,spectrum resources cannot be fully and rationally used,so we need to improve spectrum utilization.System,so as to make better use of spectrum resources and improve the utilization rate of spectrum.Therefore,on the basis of systematically combing the characteristics of satellite cognitive network and typical application scenarios of spectrum sharing,this paper analyzes the main challenges faced by spectrum sensing technology,focusing on the changing characteri stics of the signal strength to be detected in the satellite cognitive network and the satellite cognitive network.Improve the energy detection algorithm based on the uncertainty of medium noise,and consider adopting a blind detection algorithm based on the eigenvalues of the sampled covariance matrix without knowing the prior information of the cognitive user.There is a big difference between satellite communication system and traditional terrestrial communication.How to combine traditional spectrum sensing technology with GEO-LEO system is a research direction.In view of this problem,This article first introduces and analyzes several commonly used spectrum sensing technologies: the more classic energy detection algorithm(ED),the detection algorithm based on sampling covariance(MME),etc.,analyzes the application methods of spectrum sensing in each scene,and points out each the shortcomings in the algorithm and the impact they cause,analyze the advantages and disadvantages of detection algorithms under different conditions,and the specific applicable conditions.Then it briefly introduces the research of spectrum sensing mechanism.Finally,some problems faced by satellite cognitive network spectrum sensing technology are analyzed: broadband spectrum information acquisition problem,weak signal detection problem,spectrum state judgment problem,etc.Next,this article focuses on the research and analysis of the energy detection algorithm(ED)in the satellite cognitive network.The principle process and performance of the traditional energy detection algorithm are analyzed,and simulation experiments are carried out to verify its performance.Then a memory energy detection algorithm is proposed on this basis.The purpose is to deal with the problem of signal instantaneous power drop in satellite cognitive networks,and to make certain adjustments to the memory energy detection algorithm.Finally,in order to weaken the interference caused by noise uncertainty,a dual-threshold energy detection algorithm is proposed,and then simulation and analysis are performed to find its applicable scenarios.Then,we study a detection algorithm(DASCM)based on the eigenvalues of the sampling covariance matrix.It is mainly through the inference result s of related mathematical formulas to simplify the calculation,so that a relatively accurate judgment threshold can be obtained.Compared with the traditional detection algorithm,the threshold obtained by this algorithm is more accurate and reliable than the original one.Through many random experiments and simulations,we can better discover the advantages of the algorithm based on sampling covariance eigenvalues.