Research On Spectrum Sensing And Spectrum Sharing Technology In Cognitive Radio

In recent years,with the development of Internet of Things technology,the shortage of spectrum resources faced by the new generation of wireless communication technology is becoming more and more prominent.The spectrum resources are non-renewable,only by improving the utilization rate of spectrum resources,can the limited spectrum resources become more carriers of communication data and meet the explosive growth of communication data transmission needs at this stage.In cognitive radio,spectrum sensing technology and spectrum sharing technology are widely concerned.Therefore,in order to improve the utilization of spectrum resources,spectrum sensing technology and spectrum sharing technology are combined in this thesis,and a better scheme is proposed to improve the utilization of spectrum resources.The main works are as follows:Firstly,the estimation of the reliability of the nodes in the fusion center is focused on,as well,the decision fusion technology in the CR cooperative sensing is concerned in 5G.The probability and statistics method are used to estimate the detection reliability of each node.A wide-band spectrum sensing method based on the BOMP algorithm is proposed by the sparsity of the wide-band spectrum.The AIC/MDL criterion,which introduces the influence factor ??(0,1),is used to estimate the sparsity as the condition for the BOMP algorithm to stop iteration.The simulation results show that compared with the traditional OMP algorithm,the BOMP algorithm greatly improves the sensing reliability,reduces the sensing delay after introducing the influence factor.Secondly,the opportunistic spectrum access mechanism based on hierarchical spectrum sharing model is studied.Hidden Markov Chain Model(HMM)is introduced to improve the estimation of the initial state of spectrum.It provides a more reliable access opportunity for the whole spectrum sensing process and the access of secondary users,so as to improve the utilization of spectrum pool.Meanwhile,the impact of the arrival rates of primary and secondary users on the system blocking probability,forced termination probability and non-completion probability probability is studied.In the end of the thesis,the impact of the arrival rate of primary and secondary users on the capacity of secondary user system is studied.The simulation results show that after introducing reliable HMM prediction mechanism,the blocking probability and forced termination probability of primary users are effectively reduced,and the system capacity of secondary users is improved to a certain extent.