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    Coverage Analysis for UAV-Assisted Cellular Networks in Rural Areas


    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
    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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