Open Access

ARTICLE

Modeling and Analysis of UAV-Assisted Mobile Network with Imperfect Beam Alignment

Mohamed Amine Ouamri^1,2, Reem Alkanhel^3,*, Cedric Gueguen¹, Manal Abdullah Alohali⁴, Sherif S. M. Ghoneim⁵
1 University of Rennes 1/ADOPNET team at IRISA laboratory, Rennes, 35000, France
2 Faculté de Technologie, Laboratoire d’Informatique Médicale (LIMED), Université de Bejaia, Bejaia, 06000, Algérie
3 Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O.Box 84428, Riyadh, 11671, Saudi Arabia
4 Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O.Box 84428, Riyadh, 11671, Saudi Arabia
5 Electrical engineering department, College of Engineering, Taif University P. O. Box 11099, Taif, 21944, Saudi Arabia
* Corresponding Author: Reem Alkanhel. Email:

Computers, Materials & Continua 2023, 74(1), 453-467. https://doi.org/10.32604/cmc.2023.031450

Received 18 April 2022; Accepted 07 June 2022; Issue published 22 September 2022

Abstract

With the rapid development of emerging 5G and beyond (B5G), Unmanned Aerial Vehicles (UAVs) are increasingly important to improve the performance of dense cellular networks. As a conventional metric, coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment. In recent years, stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems. In this paper, an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed. An assumption was considered that all users are distributed according to Poisson Cluster Process (PCP) around base stations, in particular, Thomas Cluster Process (TCP). Using this model, the impact of beam alignment errors on the coverage probability was investigated. Initially, the Probability Density Function (PDF) of directional antenna gain between the user and its serving base station was obtained. Then, association probability with each tier was achieved. A tractable expression was derived for coverage probability in both Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) condition links. Numerical results demonstrated that at low UAVs altitude, beam alignment errors significantly degrade coverage performance. Moreover, for a small cluster size, alignment errors do not necessarily affect the coverage performance.

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Keywords

Unmanned aerial vehicles; coverage analysis; stochastic geometry; millimeter wave; imperfect beam alignment

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