Research On Bionic Intelligent Optimization Method For Secure Communication Rate Maximization In UAV Networks

Unmanned aerial vehicles（UAVs）are widely used in various fields,enabling different applications and purposes for the advantages of versatility,high mobility and flexible on-demand deployment.However,the security of the air-to-ground communications is of utmost challenge due to the broadcast nature of the wireless channels and line-of-sight links between the UAVs and ground users,and UAVs are usually resource constrained,such as their communication and airborne energy.Therefore,how to reasonably design the deployment optimization scheme of UAV to achieve safe,reliable,energy-efficient high-performance wireless communication between UAVs and their related users is very crucial for achieving its future large-scale use.This paper aims to solve this problem by using a physical layer security technology based on cooperative beamforming,specifically,this paper propose a joint optimization method of security rate,communication rate and energy efficiency based on UAV-enabled Virtual Antenna Array（UVAA）,so as to improve the secure communication of UAV network.The specific researches of this paper are as follows:（1）The physical layer security of air-to-ground communication in UAV network is realized by adopting cooperative beamforming technology.In the scene of eavesdropping nodes,the network model of virtual antenna array composed of multiple UAVs communication with the ground,the reachable secrecy rate model,UAV communication rate model and the energy loss model are constructed.When considering the deployment of the optimal UAV position and the entire flight process,the UAV not only needs to improve the communication rate and confidentiality rate with the target user,but also needs to consider reducing the mobile airborne energy consumption caused by realizing the first two objectives.（2）Using the above model,this paper constructs an optimization problem of maximizing the rate of secure communication.The constructed secret communication rate maximization problem includes three optimization objectives,namely,the secret rate of UVAA system to target users in the presence of eavesdropping nodes,the communication rate of UVAA to target users,and the airborne energy consumption of UAVs.In addition,the three optimization objectives are constructed into fitness function by linear weighting method to facilitate the solution of subsequent algorithms.Also,the problem turns out to be NP-hard.（3）An improved particle swarm algorithm（DE-PSO algorithm）combined with adaptive variation factor in difference mechanism is proposed.For the solution space of UVAADOP is too large in large scenes,the dynamically changing inertia coefficient and acceleration coefficient are proposed to improve the development ability and exploration ability of the algorithm,and adapting DE-PSO to the huge solution space of UVAADOP.Also,this paper takes advantage of the update methods of the differential evolution algorithm,and correspondingly improved efficient operator,which is conducive to the solution accuracy,so that the UVAADOP can be well settled.（4）To verify the result of the proposed algorithm,multiple groups of simulation experiments are conducted on the method using three UAV antenna array of different scales.The results show that the DE-PSO outperforms other algorithms and has better stability.It can more effectively improve the confidentiality rate and communication rate in the UAV network and cut back the airborne energy consumption of UAV.