Talgat, Anna and Kishk, Mustafa A. and Alouini, Mohamed-Slim (2021) Stochastic Geometry-Based Analysis of LEO Satellite Communication Systems. IEEE Communications Letters, 25 (8). pp. 2458-2462. ISSN 1089-7798

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Abstract

— This letter studies the performance of a low-earth-orbit (LEO) satellite communication system where the locations of the LEO satellites are modeled as a binomial point process (BPP) on a spherical surface. In particular, we study the user coverage probability for a scenario where satellite gateways (GWs) are deployed on the ground to act as a relay between the users and the LEO satellites. We use tools from stochastic geometry to derive the coverage probability for the described setup assuming that LEO satellites are placed at n different altitudes, given that the number of satellites at each altitude ak is Nk where 1 ≤ k ≤ n. To resemble practical scenarios where satellite communication can play an important role in coverage enhancement, we compare the performance of the considered setup with a scenario where the users are solely covered by a fiber-connected base station (referred to as anchored base station or ABS in the rest of the letter) at a relatively far distance, which is a common challenge in rural and remote areas. Using numerical results, we show the performance gain, in terms of coverage probability, at rural and remote areas when LEO satellite communication systems are adopted. Finally, we draw multiple system-level insights regarding the density of GWs required to outperform the ABS, as well as the number of LEO satellites and their altitudes.

Item Type:	Article
Additional Information:	Cite as: Talgat, A., Kishk, M.A. & Alouini, M. 2021, "Stochastic Geometry-Based Analysis of LEO Satellite Communication Systems", IEEE communications letters, vol. 25, no. 8, pp. 2458-2462.
Keywords:	Stochastic geometry; binomial point process; distance distribution; coverage probability;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	17593
Identification Number:	https://doi.org/10.1109/LCOMM.2020.3029808
Depositing User:	Mustafa Kishk
Date Deposited:	21 Sep 2023 14:34
Journal or Publication Title:	IEEE Communications Letters
Publisher:	IEEE
Refereed:	Yes
URI:	Publisher
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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