Wireless Coverage for Mobile Users in Dynamic Environments Using UAV

Ahmad H. Sawalmeh,Abdallah Khreishah,Hazim Shakhatreh,Noor Shamsiah Othman

doi:10.1109/access.2019.2938272

Abstract

In this paper, the dynamic deployment of a single UAV as an aerial base station in providing wireless coverage for mobile outdoor and indoor users is studied. The problem of finding the efficient UAV trajectory is formulated with the objective to minimize the required UAV transmit power that satisfies the users’ minimum data rate. The proposed solution to the problem considers the users’ movement in a search and rescue (SAR) operation. More specifically, the outdoor rescue team members are considered to move in a group with the reference point group mobility (RPGM) model. Whilst, the indoor rescue team members are considered to move individually and in a group with random waypoint and RPGM models, respectively. The efficient UAV trajectory is developed using two approaches, namely, heuristic and optimal approaches. The employment of the heuristic approach, namely particle swarm optimization (PSO) and genetics algorithm (GA), to find the efficient UAV trajectory reduced the execution time by a factor of $\simeq ~1/60$ and $\simeq ~1/9$ compared to that when using the optimal approach of brute-force search space algorithm. Furthermore, the use of PSO algorithm reduced the execution time by a factor of $\simeq ~1/7$ compared to that when the GA algorithm is invoked.The performance of the dynamic UAV deployment also outperformed the static UAV deployment in terms of the required transmit power. More specifically, the dynamic UAV deployment required less total transmit power by a factor of about 1/2 compared to the static UAV deployment, in providing wireless coverage for rescue team to perform SAR operation within a rectangular sub-region.

Highlights

Unmanned Aerial Vehicles (UAVs) have been used in many civilian applications, such as real-time monitoring, infrastructure inspection, remote sensing, search and rescue operations, delivery of goods, surveillance, precision agriculture, and to assist in providing wireless coverage [1].UAV can be used as an aerial base station as a supplement to the existing terrestrial base station when the wireless network is overloaded during a massively crowded special event, or to provide reliable communications for ground users when the infrastructure of the terrestrial base stations are damaged due to natural disasters, such as tsunami, floods and earthquake [1], [2]
The outdoor rescue team members are considered to move in a group with reference point group mobility (RPGM) model
We propose the following heuristic approach to solve this problem: 1) The subarea S is divided into n sub-regions kn = 1, 2, . . . , n, where kn denotes a sub-region with n denoting the index of each sub-region

Summary

Introduction

Unmanned Aerial Vehicles (UAVs) have been used in many civilian applications, such as real-time monitoring, infrastructure inspection, remote sensing, search and rescue operations, delivery of goods, surveillance, precision agriculture, and to assist in providing wireless coverage [1].UAV can be used as an aerial base station as a supplement to the existing terrestrial base station when the wireless network is overloaded during a massively crowded special event, or to provide reliable communications for ground users when the infrastructure of the terrestrial base stations are damaged due to natural disasters, such as tsunami, floods and earthquake [1], [2]. A. RELATED WORKS Many researches propose strategies of deploying UAV by optimizing objective functions that have different aims [1], namely, minimizing the transmit power of UAVs [3], [4], maximizing the wireless coverage of UAVs [5], minimizing the number of UAVs required to perform a given task [6], and optimizing UAV trajectory [7]. RELATED WORKS Many researches propose strategies of deploying UAV by optimizing objective functions that have different aims [1], namely, minimizing the transmit power of UAVs [3], [4], maximizing the wireless coverage of UAVs [5], minimizing the number of UAVs required to perform a given task [6], and optimizing UAV trajectory [7] Technical issues, such as endurance time is an important issue to be addressed as the duration of UAV mission is lengthened [1]. The efficient 3D deployment of UAV strategies to minimize

Objectives

Results

Conclusion