Abstract

This paper considers an unmanned aerial vehicle (UAV) base station (BS) network with delay-sensitive users and delay-tolerant users on the ground, which have different quality-of-service (QoS) requirements. In the network, the backhaul link connecting the backhaul gateway and the UAV-BS shares the same spectrum with the data links connecting the UAV-BS and the users due to spectrum scarcity. To improve the rate performance of the delay-tolerant users and to guarantee the QoS of the delay-sensitive users, we aim to maximize the minimum rate of the delay-tolerant users by jointly optimizing the bandwidths of the backhaul link and the data links, the transmit power allocated to different users and the trajectory of the UAV-BS, subject to the constraints on UAV mobility, total bandwidth, total transmit power, backhaul data rate, and minimum rate requirements of the delay-sensitive users. Although the formulated problem is non-convex and difficult to solve optimally, we propose an efficient algorithm to find a suboptimal solution to it. Simulation results show that the proposed joint optimization algorithm achieves significantly higher minimum user rate than the benchmark schemes.

Highlights

  • After decades of rapid development, unmanned aerial vehicles (UAVs) have been widely used in military, transportation, agriculture, logistics, and many other fields, and have brought a lot of changes to people’s lives, due to their advantages such as high maneuverability, easy deployment, and low cost

  • With the rising of the fifth-generation (5G) wireless communication era, UAVs have found their roles in assisting wireless communication, which help to boost the performance of 5G networks and satisfying the quality-of-service (QoS) requirements of users [1]

  • Trajectory optimization with fixed bandwidth and power allocation scheme: it fixes the bandwidths of different links and the power allocated to different users by setting x0,n = 1/2, xk,n = 1/(2K ), and pk,n = pmax/K, and optimizes the UAV trajectory by executing steps 5-10 of Algorithm 1

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Summary

Introduction

After decades of rapid development, unmanned aerial vehicles (UAVs) have been widely used in military, transportation, agriculture, logistics, and many other fields, and have brought a lot of changes to people’s lives, due to their advantages such as high maneuverability, easy deployment, and low cost. The communication performance of UAV-enabled communications can be improved by exploiting UAVs’ high mobility via appropriate trajectory design [2]–[5]. Such performance improvement can be achieved in the unmanned ground vehicle (UGV) communications [9], [10], designing UAVs’ trajectories has much fewer constraints than designing UGVs’ routes, such as obstructions and road restrictions, UAV-enabled communications have more degree of freedom in performance optimization

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