Research On Spectral Sensing Algorithm In Cognitive Radio Network

The rapid development of wireless communication technology and the fixed spectrum allocation policy have led to the shortage of spectrum resources.Cognitive radio is an emerging technology that can improve the utilization of spectrum.Its core idea is to discover "spectrum hole" through spectrum sensing technology,and allow idle users to use idle spectrum without disturbing main user communication.Therefore,fast and effective spectrum sensing is the prerequisite and basis for cognitive radio.Because of the noise uncertainty in the actual communication system and the unknown information of the authorized user,it is difficult for some traditional spectrum sensing algorithms to meet the spectrum detection needs of cognitive radio.How to efficiently detect spectrum holes under the premise of less known information becomes a hot topic in the field of cognitive radio.At present,there are three main spectrum detection algorithms: spectrum detection algorithm based on authorized user transmitter,spectrum detection algorithm based on multi-sensing user collaboration and spectrum detection algorithm based on interference temperature.Because the spectrum detection algorithm based on interference temperature is difficult to obtain the interference temperature value at the authorized user,the spectrum detection algorithm based on the authorized user transmitter and the spectrum detection algorithm based on multi-sensing user cooperation become the mainstream direction of current spectrum sensing technology research,For the different needs of the detection environment,has made a lot of research results.Although these algorithms solve the need of spectrum sensing to a certain extent,but in the process of detection,the system for environmental noise and authorized user signal characteristics and other information have different degrees of dependence,for these problems,this paper presents a different solution TheIn the first two chapters of this paper,the background and significance of spectrum sensing in cognitive radio systems are briefly described.Then,the current research situation of spectrum sensing problem is introduced,and the main problems of existing spectrum sensing algorithm are analyzed The In the second chapter,the classification and classification of spectrum and the definition and classification of spectrum are introduced.The sensing model of spectrum sensing algorithm and the analysis of performance parameters are also introduced.Based on the established perceptual model,the performance and advantages and disadvantages of energy detection,matched filter detection and cyclic stationary cycle detection are analyzed.The matching filtering method has a short detection time,but requires a priori information of the main user.The energy detection algorithm is simple to implement,But can not distinguish the signal type,and the detection time is long;Cyclic smooth detection can distinguish between signal and noise,but the complexity is high.In this paper,in order to find the available idle frequency band,the user needs to detect the presence of authorized users on each subband in a wide frequency band.However,in the face of many different types of authorized users,it is difficult for the user to know all the authorization User's signal information,so the perceived user needs a detection algorithm that can effectively detect the authorized user signal under conditions where the signal information is unknown.In this paper,we propose a detection algorithm based on generalized likelihood ratio.The algorithm estimates the unknown signal parameters.According to the Neyman-Pearson criterion,we give a test statistic that maximizes the detection probability when the false alarm probability is fixed.The simulation results show that the algorithm can effectively detect the authorized users under the condition that the signal parameters are unknown,and also show good detection performance in the lower SNR environment.In this paper,we propose a cooperative detection algorithm based on compression perceptual theory.Firstly,the system model of broadband multiuser detection is given.The estimation algorithm of channel parameters is given by using the model.And then the minimum Euclidean distance algorithm is used to estimate the authorized user's signal.The signal-to-noise ratio gain of the signal is further improved by the compression perceptual theory,so as to improve the detection performance of the perceived user.Finally,Cooperative test results.The simulation results of the proposed algorithm are analyzed under different compression ratios.The variation of the signal-to-noise ratio gain with compression ratio and signal-to-noise ratio is given,and the effectiveness of the proposed algorithm is verified.