Research On Topology Control Technology Of Cognitive Reconfiguration Network

Cognitive Radio Network extends the concept of"cognition"to the field of network,which makes wireless network have cognitive ability and reconfigurable ability.It has become one of the hottest research topics of new intelligent network.Cognitive Reconfiguration Network refers to a cognitive network that combines the idea of topological reconfiguration.It can well withstand the interference of the surrounding electromagnetic environment.Among many network technologies,the topology control of wireless network is closely related to network performance,so the research of topology control of cognitive reconfiguration network has become a hot topic in recent years.In this thesis,we firstly described the cognitive reconfiguration network and topology control technology,and then we studied the clustering algorithm of the existing topology control technology.Aiming at the characteristics of cognitive networks,this thesis optimizes the cluster head election method in order to improve the clustering performance of cognitive networks on the basis of weighted clustering WCA(Weighted Clustering Algorithms)algorithm.In this thesis,a Cognitive Topological Association-Weighted Clustering Algorithms CTA-WCA(Cognitive Topological Association-Weighted Clustering Algorithms)based on Cognitive Topological Association is proposed,and its core idea,system model,key links and simulation ideas are described.Secondly,in order to fur-ther improve the performance of the algorithm in terms of overall energy consumption and network lifetime,this thesis introduces the idea of virtual cells to optimize the clustering and topology reconstruction stages of cognitive networks based on CTA-WCA algorithm and geographic fidelity topology control algorithm.Furthermore,a new on-demand weighted clustering algorithm GCTA-WCA(Geographical Cognitive Topological Association-Weighted Clustering Algorithm)based on geographic location fidelity is proposed,and its improvement ideas,system models and key technologies are elaborated in detail.Computer simulation results show that the proposed CTA-WCA algorithm is superior to the traditional clustering algorithm in terms of energy consumption and topological stability of cluster head nodes.GCTA-WCA algorithm can further improve the average energy consumption and lifetime performance of the network.The simulation results are consistent with the theoretical expectations,which verifies the superiority of the proposed algorithm.