More than ever, there is a need for a wholly connected era, particularly for the connectivity of Internet of Things (IoT) devices dispersed across a large geographic region, including all rural, remote areas lacking suitable terrestrial infrastructure. The deployment of the low Earth orbit (LEO) satellite network is a perfect candidate to tackle this problem. Although there is a lot of work on LEO-based terrestrial communication in the literature, not all studies are appropriate for supporting IoT network technologies. The framework proposed in this article is built on stochastic geometry tools to analyze the performance of uplink of IoT over LEO satellite communication to obtain the most affordable and reliable coverage. Specifically, we investigate two different communication scenarios: In Scenario 1, the IoT device communicates directly with the satellite, while in Scenario 2, the IoT device communicates with the satellite through a gateway. We model IoT devices as Poisson cluster process on the surface of Earth and LEO constellation deployment as binomial point process at some fixed altitude above the surface of Earth. Due to the hybrid communication of the terrestrial and satellite network, we adopt Rayleigh and shadowed Rician fading for each link, respectively. Under these assumptions, the distance distributions, interference characterizations, and their Laplace transform are studied for all scenarios. Furthermore, we confirm the analytical derivation of the coverage probability with Monte Carlo simulation to analyze the proposed system's performance and present numerical results for different aspects. One of the most interesting outcomes of this study is that the Scenario 1 (direct communication) results in higher coverage probability but a lower average IoT battery lifetime compared to indirect communication.


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    Titel :

    Stochastic Geometry-Based Uplink Performance Analysis of IoT Over LEO Satellite Communication


    Beteiligte:


    Erscheinungsdatum :

    01.08.2024


    Format / Umfang :

    3548220 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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