Research On Intelligent Spectrum Access And Resource Optimization In Cognitive Radio

The rise of a new generation of wireless communication network is to meet the more complex communication needs of users.The key technologies in the network are facing problems in the development,which become the focus of people's research.Cognitive radio emerges as the times require in the rapid development of wireless communication.As one of the key technologies,its challenges and solutions become the key to the development of communication.The problem of spectrum resource shortage and low utilization rate has always existed,and with the growth of communication services,the dynamic spectrum access technology in cognitive radio can effectively alleviate the problem of spectrum resource shortage.However,in the research of current dynamic spectrum access technology,single and poor timeliness spectrum access mode can not adapt to complex communication scenarios and low user time At the same time,the efficient use of energy is becoming a key issue in the direction of green environmental protection.It is a hot issue of common concern for all walks of life to reduce energy consumption.Therefore,this paper focuses on how to improve the efficiency of spectrum utilization and energy allocation in cognitive radio.First of all,in order to improve the spectrum utilization,this paper proposes an intelligent dynamic spectrum matching model.Based on the research of Markov theory,it shows the availability and advantages of reinforcement learning algorithm in the scene of cognitive radio dynamic spectrum access.Specifically,first of all,according to the different cognitive users(CU)of the information transmission rate of the licensed user(LU),the load is judged and divided into three types.Secondly,based on the deep Q-learning network(DQN),cognitive users adjust their own power and access the authorized frequency band in three corresponding modes.Finally,we analyze the efficiency of deep reinforcement learning algorithm,and compare the theory of ergodic capacity with simulation value under dynamic spectrum matching model.The results show that the intelligent dynamic spectrum matching model can improve the timeliness of spectrum access,realize spectrum sharing under complex load scenarios of authorized users,improve the spectrum utilization rate,improve the ergodic capacity of authorized users,and reduce the impact on the normal communication of authorized users under spectrum sharing.In order to improve the system performance and reduce the energy consumption,this paper further optimizes the existing energy distribution of the system,introduces the technology of wireless information and power transfer(SWIPT),and discusses its role in data and energy transmission under the dynamic spectrum matching mode.Firstly,this paper proposes the expression of time as a variable in the energy storage phase of wireless energy carrying communication.Compared with the general energy storage,energy conversion factor is added,and the relationship between time and energy storage is used to quantify energy,which is more in line with the general definition of energy storage in theory.Secondly,the ergodic capacity of the dynamic spectrum matching model system is analyzed.Finally,two typical energy collection protocols in wireless energy carrying technology are compared,and the efficiency of the protocol under the same conditions is discussed.The results show that wireless energy carrying communication technology is integrated into dynamic spectrum matching,which provides more choices for energy expenditure and makes energy allocation and utilization more reasonable.