Analyzing The Algorithm Of Cooperative Cognitive Radio Technology On VANET

With the rapid development of wireless communication technologies and modem car manufactures, Intelligent Transportation System (ITS) emerges as the times require. As the key technology of Intelligent Transportation System, Vehicular Ad hoc Networks (VANET) has attracted more and more attentions. Limited by spectrum resource scarcity, the VANET could not be allocated special frequency band so that spectrum scarcity became the key problems which restrict the development of the vehicle ad-hoc network technology. Recently, studies demonstrate that Cognitive Radio (CR) technology can increase the spectrum efficiency of wireless systems, provided that the activity of primary users (PUs) so that the CR has emerged as the key solution to support the increasing demand of spectrum for wireless communications, through the implementation of the opportunistic spectrum sharing paradigm. However in the special VANET scenario, the fast speed of vehicles, frequent changes of network topology and unstable wireless channel create a series of challenges on detecting the spectrum holes. How to sense spectrum holes accurately and timely in high-speed VANET environments becomes the key issue in CR-VANETs. The main contents and contribution of this thesis are as follows:(1) Based on deep analyses research on the directions of CR-VANETs and relevant architectures, targeted at the status of the research about spectrum sensing on CR-VANETs to establish the research plan.(2) Studied the traditional spectrum sensing algorithm of cognitive radio technology, and analyzed the shortage of the single-node spectrum sensing algorithm and the superiority of the collaborative perception algorithm by combination of theory and simulation. Analyses the effects on the sensing performance of the diagram of the energy sensing by simulation. Filtering algorithms which have better performance through comparing the collaborative perception algorithms which include hard decision algorithms and soft decision algorithms by simulation at static scenario.(3) In this thesis established a scenario model, highway scenario model that assuming the communication model and the model of the vehicle’s movement based on the characteristics of VANET to examining the performance of traditional spectrum sensing algorithms. Analyzed the MRC, EGC and data fusion algorithm by "or" rule based on simulation at VANET scenarios, mainly considers the impact to sensing performance caused by the movement of vehicles and the dynamic fading channel at real environment. The results of simulation demonstrate that the performance of MRC is better than other two algorithms. The effect on the detection performance caused by vehicle’s high-speed movement is uncertain.(4) Clustering cooperative spectrum sensing algorithm based on particle swarm optimization is introduced in this thesis. Particle swarm optimization is used to optimize the calculation of the weights, to improve the traditional algorithm MRC as the result of the performance of MRC is unsatisfactory at VANET scenario. With the method of clustering which omit the result of the vehicles which has poor channel quality, to reduce the impact of vehicle node with bad channel quality. But the results of simulation show that deleted information will cause the loss of cognitive performance so that need to ameliorate the algorithm. The ameliorated algorithm that judgment in the clusters first and then the cluster head broadcast the results to the fusion center, the fusion center node judge based on "or" rule.