Dynamic Spectrum Allocation Strategy In CRN Based On Sensing Users Classification And Its Performance Optimization

The rapid development of the Internet of Things has brought a large number of communication demands,which makes the limited spectrum resources increasingly short.In order to alleviate the contradiction between supply and demand of spectrum resources,Cognitive Radio Network(CRN)has been widely used.In order to improve the utilization of spectrum resources and meet the differentiated transmission requirements of sensing users,sensing users are divided into class Ⅰ sensing users and class Ⅱ sensing users,and the dynamic spectrum allocation strategy and performance optimization of CRNS for sensing users classification are studied.Firstly,in order to improve the flexibility of spectrum allocation and reduce the interference between primary users and sensing users,a dynamic spectrum allocation strategy combining two pools and sensing user classification is proposed.In order to improve the service quality of class Ⅰ sensed users,a reserved spectrum pool is set for preempted class Ⅰ sensed users,and a dynamic spectrum allocation strategy is proposed that integrates the reserved spectrum pool and sensed user class.Secondly,aiming at the dynamic spectrum allocation strategy combining two pools and perceptive user classification,a preemption priority continuous time queuing model with three types of users is established.According to the number of primary users and two types of sensing users in the spectrum pool,a six-dimensional Markov chain is constructed.Aiming at the dynamic spectrum allocation strategy that integrates the reserved spectrum pool and the perceptive user classification,the preemption priority queuing model integrating the three types of users and the low speed reserved service desk is established.According to the number of primary users and two types of sensing users in the spectrum pool,the seven-dimensional Markov chain is constructed.Thirdly,steady-state analysis of queuing model is carried out to deduce the expression of sensing users blocking rate and traffic drop rate,perceived users and primary users’ throughput.Based on the established queuing model,the numerical experiments show that the performance indexes of class Ⅱ sensing users change with the arrival rate and service rate of primary users,class Ⅰ sensing users and class Ⅱ sensing users,and verify the effectiveness of the spectrum allocation strategy.The proposed strategy is simulated to verify the rationality of the queuing model.Finally,combining the return and cost,we construct the individual benefit function and the social benefit function respectively for the two kinds of sensing users.Using Circle mapping chaos method to improve particle swarm optimization algorithm,Nash equilibrium arrival rate and social optimal arrival rate for two kinds of dynamic spectrum allocation strategies are given respectively.In order to maximize the social benefits of the system,channel pricing schemes are developed for two kinds of sensing users according to different arrival rates of primary users.