Aerial Base Station Placement: A Tutorial Introduction

Viet, Pham Q.; Romero, Daniel

doi:10.1109/mcom.001.2100861

Cited by 12 publications

(4 citation statements)

References 15 publications

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“…The development of unmanned aerial vehicle technology has allowed their application in different areas. In [9], the main applications of UAVs in wireless sensor networks are examined and divided them into three categories: auxiliary data gathering, collaborative sensing, and autonomous deployment. Each category is discussed in detail along with engineering application examples.…”

Section: Related Workmentioning

confidence: 99%

“…UAVs in systems with an aerial BS are being developed to provide internet connectivity in areas without sufficient terrestrial infrastructure, such as remote locations or areas affected by natural disasters. In the article [9], the aerial BS placement problem is introduced and explored, and the trade-offs and challenges associated with it are discussed. The article also presents various approaches to addressing these challenges in 2D and 3D spaces, and the concept of adaptive placement is discussed.…”

Section: Related Workmentioning

confidence: 99%

“…To overcome the challenges of information transfer over long distances, unmanned aerial vehicles (UAVs) are suggested as a solution for WSNs [9]. With their mobility and adaptive altitude, UAVs can act as a wireless mobile backbone to collect information from the ground sensors and transmit it to a BS for analysis.…”

Section: Introductionmentioning

confidence: 99%

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Availability of Services in Wireless Sensor Network with Aerial Base Station Placement

Kabashkin

2023

JSAN

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Internet of Things technologies use many sensors combined with wireless networks for cyber-physical systems in various applications. Mobility is an essential characteristic for many objects that use sensors. In mobile sensor networks, the availability of communication channels is crucial, especially for mission-critical applications. This article presents models for analyzing the availability of sensor services in a wireless network with aerial base station placement (ABSP), considering the real conditions for using unmanned aerial vehicles (UAVs). The studied system uses a UAV-assisted mobile edge computing architecture, including ABSP and a ground station for restoring the energy capacity of the UAVs, to maintain the availability of interaction with the sensors. The architecture includes a fleet of additional replacement UAVs to ensure continuous communication coverage for the sensor network during the charging period of the air-based station UAVs. Analytical expressions were obtained to determine the availability of sensor services in the system studied.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Availability of Services in Wireless Sensor Network with Aerial Base Station Placement

Kabashkin

2023

JSAN

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“…Users on the ground, here referred to as ground terminals (GTs), are served by ABSs, which in turn connect to the terrestrial infrastructure through backhaul links, possibly in multiple hops through other UAVs that act as relays. Deploying ABSs involves addressing the problem of ABS placement, where one is given the locations of the GTs and must decide on a suitable set of spatial positions for the ABSs to effectively serve the GTs [3]. This task is typically hindered by several challenges, remarkably (C1) the uncertainty in the gain of the propagation channel between the GTs and the potential ABS locations, (C2) the limited…”

Section: Introductionmentioning

confidence: 99%

Aerial Base Station Placement via Propagation Radio Maps

Romero¹,

Viet²,

Shrestha³

2023

Preprint

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The technology of base stations on board unmanned aerial vehicles, also known as aerial base stations (ABSs), promises to deliver cellular connectivity in areas where the terrestrial infrastructure is overloaded, damaged, or inexistent. A central problem in this context is to determine the locations where these ABSs must be deployed to serve a set of users on the ground given the positions of the latter. However, existing schemes assume that the channel gain depends only on the length and (possibly) the elevation of the link. To alleviate this limitation, this paper proposes a scheme that accommodates arbitrary channel gains by means of a propagation radio map of the air-to-ground channel. The algorithm finds the locations of an approximately minimal number of ABSs to serve all ground terminals with a target rate while meeting the given constraints on the capacity of the backhaul links and respecting no-fly regions. A convex-relaxation formulation ensures convergence and the alternating-direction method of multipliers is utilized to derive an implementation whose complexity is linear in the number of ground terminals. Numerical results with tomographic as well as ray-tracing channel models corroborate the strengths of the proposed scheme.

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