Abstract

In recent years, due to the strong mobility, easy deployment, and low cost of unmanned aerial vehicles (UAV), great interest has arisen in utilizing UAVs to assist in wireless communication, especially for on-demand deployment in emergency situations and temporary events. However, UAVs can only provide users with data transmission services through wireless backhaul links established with a ground base station, and the limited capacity of the wireless backhaul link would limit the transmission speed of UAVs. Therefore, this paper designed a UAV-assisted wireless communication system that used cache technology and realized the transmission of multi-user data by using the mobility of UAVs and wireless cache technology. Considering the limited storage space and energy of UAVs, the joint optimization problem of the UAV’s trajectory, cache placement, and transmission power was established to minimize the mission time of the UAV. Since this problem was a non-convex problem, it was decomposed into three sub-problems: trajectory optimization, cache placement optimization, and power allocation optimization. An iterative algorithm based on the successive convex approximation and alternate optimization techniques was proposed to solve these three optimization problems. Finally, in the power allocation optimization, the proposed algorithm was improved by changing the optimization objective function. Numerical results showed that the algorithm had good performance and could effectively reduce the task completion time of the UAV.

Highlights

  • The performance of the ITE algorithm and the IMP algorithm are compared by using the straight line flight optimization (SLF) [36] and the trajectory optimization scheme (TOS) [34]

  • The unmanned aerial vehicles (UAV) can pre-store a part of popular content to provide users with data transmission services

  • Considering the limited storage space, the goal is to minimize the time for the UAV to serve users by jointly optimizing cache placement, the UAV’s trajectory and transmission power under the constraints of maximum energy estimation and data requirements for each user

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Summary

Introduction

Many countries are using fifth-generation (5G) mobile communications in commercial deployments, and the industry, academia, and regulatory agencies have begun to research and develop next-generation mobile communication networks. As one of the access methods of the sixth-generation (6G) mobile communication network, UAVs are paramount to the goal of building an integrated air-space–ground–sea network to achieve emergency coverage, depth of coverage, and breadth of coverage [1,2,3]. Networked robotics and autonomous systems are typical applications of 6G, and UAV delivery systems are an example. Using drone technology in 6G would help achieve cellular-free communications [4]. UAVs will become important elements in 6G wireless communication, and, the research on UAV communication systems and related technologies has strategic significance [5]

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