Research On Cooperative Spectrum Sensing Algorithms For Cognitive Radio

The shortage of spectrum resources has increasingly become the biggest obstacle to the development of wireless communication technology.Especially in this era of information explosion,the increasing number of mobile terminals and the higher requirements for information transmission speed make the shortage of spectrum resources increasingly prominent.However,it is found that the utilization rate of spectrum resources is very low.The reason is due to the current backward and fixed spectrum allocation system.However,with the continuous development of communication technology,some services with spectrum usage rights and backward technology have been eliminated,while emerging technologies urgently need effective spectrum resources to achieve service transmission.Using cognitive radio technology,users can dynamically sense the surrounding environment,detect the idle spectrum and access to achieve communication.The core of cognitive radio technology is spectrum sensing,which can judge whether there are authorized users in the target frequency band.It is the precondition of using cognitive radio technology to complete communication.Therefore,spectrum sensing algorithm has a wide range of research value.The main work and innovations of this paper are as follows:(1)The development and current situation of cognitive radio technology are introduced,and the advantages and disadvantages of different kinds of spectrum sensing algorithms are emphatically analyzed.(2)There is always a contradiction between high detection probability and low false alarm probability in cognitive networks.Based on the analysis of decision threshold derived from maximum eigenvalue limit distribution and minimum eigenvalue limit distribution of sampling covariance matrix,a threshold weighted cooperative spectrum sensing algorithm is proposed.The final decision threshold of the proposed algorithm is determined by weighting method,that is,the detection performance of the system is optimized by assigning weights to the threshold value.Through simulation analysis,the detection probability of the proposed algorithm is higher than that of MME algorithm,and the false alarm probability is obviously lower than that of NMME algorithm.(3)Because the detection performance of each cognitive user is different in the process of participating in perception,if the perception results are transmitted to the data fusion center in an equally important way,it will have a great impact on the final decision results of the system.In view of this,this paper proposes a weighted method to improve the traditional Krank criterion.Each cognitive user's decision results are assigned different weight values,which represent the difference of detection performance of cognitive users.That is,the higher the signal-to-noise ratio(SNR)of the received signal,the larger the weight value.Then it is transmitted to the data fusion center to participate in the final decision.(4)A cooperative spectrum sensing algorithm based on improved dual-threshold energy detection is proposed.The algorithm mainly divides a complete spectrum sensing process into three stages until the system makes an accurate decision.Specifically,in the first stage,the dual threshold energy detection algorithm is used for detection;in the second stage,the improved K-rank criterion algorithm is used for detection;and in the third stage,the threshold-weighted cooperative spectrum sensing algorithm proposed in this paper is used to complete the detection.Definitely.Only when the previous stage of judgment fails and the exact result of judgment cannot be given,will it be automatically transferred to the next judgment.The purpose of this design is to improve the traditional K-rank criterion as a hard decision method,which has the advantages of low system overhead and short sensing period.At the same time,it also takes advantage of the high detection probability of cooperative spectrum sensing algorithm system based on threshold weighting.The simulation results show that the proposed algorithm can effectively improve the detection performance of the system,which shows that the research ideas in this paper are correct.