Research On Optimal Transmission Strategy Of UAV Cooperative Communication System Oriented To Data Acquisition

As a flexible mobile platform,Unmanned Aerial Vehicle(UAV)can work with Wireless Sensor Network(WSN)to provide data collection functions.With the development of UAV and sensor technology,UAV-assisted WSN data acquisition has attracted more and more attention.By using the air-ground link for data collection,it is not limited by the mobility of ground vehicles,avoiding the signal attenuation problem caused by the ground communication link being blocked by buildings,and improving the data collection rate of the entire system.In particular,the optimization of UAV trajectories provides an important new design freedom for improving data collection performance and opens a new research paradigm for the co-design of UAV trajectory and WSN communication.However,with the expansion of the scale and time complexity of this kind of collaborative design problem,the difficulty of dealing with the problem also shows a trend of rapid growth.In addition,with the development of artificial intelligence supported by big data,sensors are widely deployed in scenarios such as intelligent transportation,forest monitoring,and smart cities.challenge.Based on the above problems,this paper studies the UAV communication collaborative design transmission system for data collection.And according to the WSN communication requirements,a new general framework is designed for UAV trajectory and communication collaborative design to achieve reliable data acquisition while reducing the problem scale.The main research content and innovation points of this paper are as follows:Aiming at the difficulty of collecting high-density data of WSN and the complex scale of collaborative design,an optimization strategy for UAV communication transmission based on flexible path discrete method is proposed.This strategy first transforms the original continuous domain problem into a linear state space problem through the flexible path discretization method,and divides the UAV trajectory into designable waypoints and non-designable waypoints to reduce the problem scale.Second,to overcome the limitations of data collection in complex geographical environments,the strategy uses a probabilistic line-of-sight channel model and formulates the problem as a non-convex joint optimization problem of communication scheduling and three dimensional trajectories.By adopting multiple convex optimization methods to decouple the original problem into blocks,and optimize it alternately,the optimal solution of the problem is obtained.Simulation results show that this strategy can effectively collect highly dense data and reduce the scale of collaborative design.At the same time,this strategy can also be effectively applied to complex geographical environments such as cities,and improve data collection efficiency by optimizing UAV communication transmission.Aiming at the problem of less data collection and limited coverage of a single UAV,a data acquisition-oriented multi-UAV communication transmission optimization strategy based on the receding horizon method is proposed,aiming to achieve reliable data collection through the characteristics of Rice fading channels.At the same time,in order to reduce the problem size and task completion time,this study designs a general framework based on the receding horizon method,which is suitable for multiUAV communication collaborative design.The constructed original problem is decoupled into three sub-problems.The scheduling allocation optimization subproblem is solved by standard convex optimization,and the UAV horizontal trajectory and UAV vertical trajectory optimization subproblems are solved by continuous convex approximation method under the relaxed constraints.Finally,the block coordinate descent algorithm is used to alternately optimize the scheduling allocation and threedimensional trajectory to solve the original problem.The simulation results show that under the condition of ensuring a certain interruption probability for each user,the problem of UAV data receiving distance limitation can be overcome,thereby effectively improving the multi-UAV WSN data collection capability.