| Spectrum sensing is the key to CR technology and used to detect the available channels in the licensed spectrum.Effectively detecting the active state of the PU is important for the utilization of limited spectrum resources.Cooperative spectrum sensing can effectively solve the problem of unreliable single node sensing,but on the other hand,it also increases network energy consumption.At the same time,when there are malicious users among SUs,it not only increases the additional communication overhead of the CRSNs,but also interferes with other SUs,which leads to a decline in the performance of the entire network.Therefore,it is especially important to optimize existing cooperative spectrum sensing solutions to detect and remove malicious users.This thesis will focus on energy consumption optimization in cooperative spectrum sensing scenarios in CRSNs.The main work and innovations are as follows:(1)Firstly,this thesis analyzes the origin of CR technology,the problems encountered in its development,and determines the key research indicators of energy consumption optimization.Secondly,it focuses on the analysis of node selection in CSS in the existing works.Finally,the thesis focuses on the analysis of spectrum sensing energy optimization at home and abroad.(2)An optimal spectrum sensing node ratio scheme is proposed,which optimizes the traditional network topology and solves the problem of the optimal number of spectrum sensing nodes under different node densities in the network.Experimental results show that the scheme can achieve the goal of effectively reducing network energy consumption and extending network lifetime.(3)An energy-efficient spectrum sensing scheme based on D-S evidence theory is proposed.The representative node selection strategy solves the contradiction between spectrum sensing accuracy and network energy consumption.Experimental results show that the method improves the accuracy of spectrum sensing and reduces network energy consumption. |
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