Matracia, Maurilio, Kishk, Mustafa A. and Alouini, Mohamed-Slim (2021) Coverage Analysis for UAV-Assisted Cellular Networks in Rural Areas. IEEE Open Journal of Vehicular Technology, 2. pp. 194-206. ISSN 2644-1330
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Abstract
Despite enhancement in rural areas is one of the main requirements in next generations of
wireless networks (i.e., 5G and 6G), the low expected profit prevents telecommunication providers from
investing in such sparsely populated areas. Hence, cost efficient alternatives are required for extending
the cellular infrastructure to these regions. A concrete mathematical model that characterizes and clearly
captures the aforementioned problem might be a key-enabler for studying the efficiency of any potential
solution. Unfortunately, the commonly used mathematical tools that model large scale wireless networks
are not designed to capture the unfairness, in terms of cellular coverage, suffered by exurban and rural
areas. In big cities, in fact, cellular deployment is essentially capacity driven and thus cellular base station
densities are maximum in the town centers and decline when getting far from them. In this paper, a new
stochastic geometry-based model is implemented in order to show the coverage spatial variation among
urban, suburban, and exurban settlements. Indeed, by implementing inhomogeneous Poisson point processes
(PPPs) it is possible to study the performance metrics in a realistic scenario where terrestrial base stations
(TBSs) are clustered around the urban center while outer aerial base stations (ABSs) are uniformly distributed
outside an urban exclusion zone. Based on this, our simulation results can quantify the improvement, in
terms of coverage probability, that even a surprisingly low density of ABSs can bring to peripheral regions
depending on the extension of the exclusion zone, enabling us to draw insightful considerations.
Item Type: | Article |
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Keywords: | Stochastic geometry; Poisson point process; coverage probability; UAV; rural areas; |
Academic Unit: | Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 16973 |
Identification Number: | 10.1109/OJVT.2021.3076814 |
Depositing User: | Mustafa Kishk |
Date Deposited: | 28 Feb 2023 15:23 |
Journal or Publication Title: | IEEE Open Journal of Vehicular Technology |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/16973 |
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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