Research On Low-delay Information Transmission Optimization Method For Joint Communication And Computation System Of The Uav Swarm

Unmanned aerial vehicles(UAVs)have been widely deployed for environmental monitoring,firefighting,disaster rescue and other scenarios due to their rapid deployment and flexible mobility.However,the utmost challenge is how to transfer the important and urgent information to the control center as quick as possible in face of communication and payload constraints.The use of mobile edge computing(MEC)on UAVs is expected to support computation-intensive and latency-critical applications.Therefore,in this thesis,a joint communication and computation model is established for a MEC enabled UAV network,and the optimization method of information transmission with low delay is studied.The main contributions of this thesis are as follows:(1)Aiming at the problem that the information collected by the UAV cannot be efficiently transmitted to the control center,a centralized joint communication and computation model is proposed.Using stochastic geometry,the successful transmission probability results for a single link and a group of links are derived based on the three-dimensional distribution of UAV swarm.Moreover,the optimal response delay is theoretically achieved with the closed-form solutions by using stochastic geometry and queueing theory.The response delay optimization algorithm is designed.Simulation results show that the proposed response delay optimization algorithm can reduce the delay by 10%-20%compared with the traditional algorithm.(2)Aiming at the problem that UAV cannot meet the diversify latency-critical applications requirements,the distributed model includes the cloud service support(CSS)UAVs and the local service support(LSS)UAVs is proposed.For CSS UAVs,the enhanced collaborative computing model is designed and the closed-form solution of the decision threshold is also achieved by using queueing theory.For LSS UAVs,the system status update algorithm is proposed based on the age of information(AoI).The software simulation and hardware platform are designed to verify the algorithm proposed in this thesis.The results show that the proposed method can effectively reduce the response delay by 23%and improve the information timeliness by 20%.