Research On Improvement Of Energy Efficiency And Security In Cellular Vehicular Networks

With the widespread use of mobile internet,internet of things,and wireless sensor network technologies,the vehicular network is considered as the main application scenario of 5G,which will realize the connections of vehicle-to-vehicle,vehicle-to-road,vehicle-to-pedestrian.Cellular vehicular network consists of macro cells,roadside units and vehicles,which can increase the spectrum utilization and network energy efficiency to meet the ultra-reliable and low-latency scenario requirement of 5G vehicular network by the C-V2 X technology and the LTE network.This thesis focuses on energy efficiency of the network under the loading balance,fairness of spectrum resource allocation and average network outage probability constriant.In addition,the roadside unit in cellular vehicular network could be attacked and become a malicious roadside unit.It will broadcast wrong information to the local service center,and cause the decreasing of network energy efficiency.Based on this,this thesis studies the problem of malicious roadside unit detection and resource allocation optimization to maximize the energy efficiency of the cellular vehicular network.This thesis studies energy-efficient resource allocation problem in cellular vehicular networks.Firstly,in the network model,vehicles could dynamically select transmission relays based on the transmission quality.To obtain the optimal match between the vehicle and the resource block while ensuring the loading balance of the network,an energy-efficient resource allocation algorithm is proposed.Secondly,if there are more than one vehicles compete for the same resource block,to ensure the fairness resource allocation among vehicles,an auction based vehicle and resource block matching algorithm is proposed.The matching relationship between different vehicles and resource blocks is depended on the matching degrees.Finally,we optimize the vehicle transmission power to further improve network energy efficiency.Simulation results show that the proposed algorithm can achieve loading balance of the network,guarantee the average probability of the network outage while ensuring the trade-off between the network energy efficiency and the fairness between vehicles.Besides,due to the remote location of some roadside units,which cannot be timely maintained by the network administrator,they may be attacked and become untrustworthy roadside units,resulting in a reduction in vehicle communication quality and network energy efficiency.In order to ensure the security of user data,this thesis proposes a trust degree based roadside unit recognition and resource allocation algorithm.The algorithm models roadside unit recognition,transmission mode selection and power allocation jointly as a network energy efficiency optimization problem,and divides it into three sub-optimization problems to be solved separately.First,the RSU recognition algorithm based on trust degree is used to identify trusted and untrusted roadside units;secondly,the vehicle resource block configuration and link selection are optimized;and finally,the subgradient algorithm is used to optimize the transmission power and maximize the network energy efficiency.Theoretical analysis and simulation results show that the proposed algorithm has lower complexity,can achieve higher recognition accuracy of roadside units,and effectively improve the overall energy efficiency of the network.