Research On Resource Allocation Method In UAV-Assisted WSN Data Collection

In the traditional wireless sensor network(WSN),the ground terminal can only rely on wireless multi-hop to transmit data to the base station.A large amount of redundant data transmission not only causes the ground terminal to generate great energy consumption,but also The data transmission delay cannot be guaranteed.In special scenarios such as mountainous areas and post-disasters,the deployment of ground base stations also faces many difficulties.With the rapid development of drone technology,by installing a wireless communication module on the UAV to act as a mobile aerial base station,the ground terminal can upload data to the drone through single-hop wireless information transmission to achieve the purpose of WSN data collection.So as to effectively solve the problem of lack of ground network communication resources.In addition,considering the limited battery power of the ground terminal,extending the life cycle of the network has always been an important goal of WSN.In the above scenario,it is inconvenient to replace the battery of the ground terminal and the cost is very high.This paper proposes that by installing a wireless charging module on the drone at the same time as a mobile energy source,wireless energy transmission technology can be used to compensate for the energy consumption of the ground terminal,thereby effectively extending the life cycle of the ground network.The realization of UAV-assisted data collection and wireless charging faces many theoretical and technical challenges,including: UAV flight trajectory planning,flight parameter control,wireless energy transmission and wireless information transmission working time allocation,etc.The ultimate goal is to minimize the completion time of data collection tasks or reduce the overall energy consumption of ground terminals and drones.Based on the above analysis,the specific research content of this article is as follows:Study 1: In open areas,such as open fields,large areas of arable land,etc.,since the communication link between the drone and the ground terminal is line-of-sight,this article first assumes that the channel model between the UAV and the ground terminal is the line-of-sight channel model.In addition,this article considers that the UAVassisted wireless energy transmission system adopts a linear energy capture model,and the energy conversion efficiency of the energy capture module is independent of the input power level.In this paper,the UAV’s flight trajectory,wireless energy transmission and wireless information transmission time allocation are jointly optimized to minimize the time to complete the data collection task.This problem is a mixed integer nonlinear programming problem,which is difficult to solve with standard methods.For this reason,this paper develops an iterative algorithm based on binary search and continuous convex optimization to find the sub-optimal solution of the problem.Through a series of comparative simulations,the effectiveness of the proposed algorithm is verified.Study 2: In urban,rural and complex application scenarios,because the communication link between the drone and the ground terminal is usually blocked by obstacles,a hybrid link of line-of-sight and non-line-of-sight is formed.This paper adopts the Rice fading channel model Describe the wireless channel characteristics of UAV and ground terminal.In addition,considering that the energy conversion efficiency of the actual energy capture module will vary with the input power,this article adopts a more practical nonlinear energy capture model.Through joint optimization of the UAV’s flight trajectory,wireless energy transmission and wireless information transmission time allocation,the data collection task completion time when there are communication link obstacles is minimized.By decoupling the problem into three sub-problems,and using continuous convex optimization technology to transform the non-convex sub-problems into convex sub-problems,iterative solution.Through the performance comparison with the line-of-sight channel model and the linear energy capture model,it is verified that the Rice fading channel model and the nonlinear energy capture model can better evaluate the performance of the UAV-assisted WSN data collection system.