The Research On Spectrum Cooperative Sensing In Heterogeneous Network

The flourishing development of communication technology has brought about the coexistence of various kinds of heterogeneous communication networks.The explosive growth of the user's business also puts forward higher requirements for the spectrum utilization performance.As a strategy to ease the shortage of spectrum resources,the emergence of cognitive radio technology has brought new opportunities for the intelligent fusion of heterogeneous networks.Heterogeneous cognitive radio network,which is considered as a development trend for the future network,has unique abilities and advantages.However,the research on how to improve the performance of cognitive technology in future heterogeneous cognitive radio network is still to be strengthened.As the key technology of cognitive radio,spectrum sensing should be inevitably paid more attention.Based on the above purposes,this paper firstly proposes a method of clustering cooperative spectrum sensing algorithm based on joint weight.By considering the heterogeneous characteristics of primary and secondary users,a more practical method to meet the actual heterogeneous cognitive network scenario is established.On the basis of the analysis of the current research and key issues,the algorithm pays attention to the scheduling of the secondary users,that is,how to allocate multiple secondary users to perceive multiple authorized users.Then the concept of joint weight is put forward,and the clustering process of the algorithm is introduced in details.Finally,the specific steps of cooperative sensing and the related performance evaluation index are described.Simulation results show that the new algorithm can effectively improve the performance of the network and realize the self-adaptive configuration.In addition,this paper builds a heterogeneous cognitive system level simulation platform.The overall framework,simulation flow and parameter configuration of the simulation platform are introduced and the related simulation results are given.The platform provides an effective way to evaluate the performance of the related cognitive radio technology in heterogeneous networks.