UAV-Enabled Data Collection: Multiple Access, Trajectory Optimization, and Energy Trade-Off

Chenfan Weng,Dingcheng Yang,Yipeng Liang,Qingmin Zhao,Lin Xiao

doi:10.1155/2019/9647539

Chenfan Weng, Dingcheng Yang + Show 3 more

Open Access

https://doi.org/10.1155/2019/9647539

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Abstract

In this paper, we consider a ground terminal (GT) to an unmanned aerial vehicle (UAV) wireless communication system where data from GTs are collected by an unmanned aerial vehicle. We propose to use the ground terminal-UAV (G-U) region for the energy consumption model. In particular, to fulfill the data collection task with a minimum energy both of the GTs and UAV, an algorithm that combines optimal trajectory design and resource allocation scheme is proposed which is supposed to solve the optimization problem approximately. We initialize the UAV’s trajectory firstly. Then, the optimal UAV trajectory and GT’s resource allocation are obtained by using the successive convex optimization and Lagrange duality. Moreover, we come up with an efficient algorithm aimed to find an approximate solution by jointly optimizing trajectory and resource allocation. Numerical results show that the proposed solution is efficient. Compared with the benchmark scheme which did not adopt optimizing trajectory, the solution we propose engenders significant performance in energy efficiency.

Highlights

With series of features such as low cost, long duration, high exibility, and high adaptability, extensive research endeavour has been rendered to exploring the application of unmanned aerial vehicle (UAV)
For UAV’ flying, the steady level flight would be a better choice for energy decreasing. It motivates our investigation of the following question: what are the optimal UAV flying trajectory strategies for data transmission and UAV flight energy consumption? To answer this question, we propose to use ground terminal-UAV (G-U) region for the energy consumption model to characterize all the ground terminal transmit power and UAV energy consumption pairs under a given data collection rate constraint
We first formulate the optimization problem to describe the Pareto boundary of the energy region. en, we investigate the optimal solution of the optimization problem for this scenario, from which we obtain an upper bound for the achievable energy consumption pairs in the G-U region. en, we propose an alternating iterative method to derive the optimal resource allocation scheme and optimal trajectory design strategy

Summary

Introduction

With series of features such as low cost, long duration, high exibility, and high adaptability, extensive research endeavour has been rendered to exploring the application of UAV. In [1], the authors made a survey on autonomous cargo pickup with an UAV helicopter by designing systems including self-tracking, payload pickup, and deployment of cargo. Researchers are trying to solve these problems. It can be hired for delivery of goods, and serve as low-altitude aircraft to improve the coverage and rate of wireless networks in di erent scenarios. Us, in [12], the authors propose an efcient deployment method based on circle packing theory, using minimum transmit power and maximizing the total coverage area. Bor-Yaliniz et al [13] emphasized the performances of drone-cell placement problem by designing it as a 3D placement that leads to maximum revenue of the network. UAV’s energy e ciency and resource management are crucial factors in its communication systems. ere are many di erences between traditional wireless communication system and UAV communication

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