Matracia, Maurilio, Kishk, Mustafa A. and Alouini, Mohamed-Slim (2023) UAV-Aided Post-Disaster Cellular Networks: A Novel Stochastic Geometry Approach. IEEE Transactions on Vehicular Technology, 72 (7). pp. 9406-9418. ISSN 0018-9545
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Official URL: https://doi.org/10.1109/TVT.2023.3247920
Abstract
Motivated by the need for ubiquitous and reliable
communications in post-disaster emergency management systems
(EMSs), we hereby present a novel and efficient stochastic geometry
(SG) framework. This mathematical model is specifically designed
to evaluate the quality of service (QoS) experienced by a typical
ground user equipment (UE) residing either inside or outside a
generic area affected by a calamity. In particular, we model the
functioning terrestrial base stations (TBSs) as an inhomogeneous
Poisson point process (IPPP), and assume that a given number of
uniformly distributed unmanned aerial vehicles (UAVs) equipped
with cellular transceivers is deployed in order to compensate for the
damage suffered by some of the existing TBSs. The downlink (DL)
coverage probability is then derived based on the maximum average
received power association policy and the assumption of Nakagamim fading conditions for all wireless links. The proposed numerical
results show insightful trends in terms of coverage probability, depending on: distance of the UE from the disaster epicenter, disaster
radius, quality of resilience (QoR) of the terrestrial network, and
fleet of deployed ad-hoc aerial base stations (ABSs). The aim of
this paper is therefore to prove the effectiveness of vertical heterogeneous networks (VHetNets) in emergency scenarios, which can
both stimulate the involved authorities for their implementation
and inspire researchers to further investigate related problems.
Item Type: | Article |
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Keywords: | Coverage analysis; stochastic geometry; binomial point process; UAVs; quality of resilience; post-disaster communications; |
Academic Unit: | Faculty of Science and Engineering > Electronic Engineering |
Item ID: | 18622 |
Identification Number: | 10.1109/TVT.2023.3247920 |
Depositing User: | Mustafa Kishk |
Date Deposited: | 07 Jun 2024 14:14 |
Journal or Publication Title: | IEEE Transactions on Vehicular Technology |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/18622 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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