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JCR Impact Factor: 0.700
JCR 5-Year IF: 0.700
SCOPUS CiteScore: 1.8
Issues per year: 4
Current issue: Nov 2024
Next issue: Feb 2025
Avg review time: 55 days
Avg accept to publ: 60 days
APC: 300 EUR


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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LATEST NEWS

2024-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

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  4/2024 - 6

Phased Antenna Arrays, Software Defined Radio and Artificial Intelligence: Advancing LEO Satellite Communications

ADOMNITEI, C.-I. See more information about ADOMNITEI, C.-I. on SCOPUS See more information about ADOMNITEI, C.-I. on IEEExplore See more information about ADOMNITEI, C.-I. on Web of Science, LESANU, C.-E. See more information about  LESANU, C.-E. on SCOPUS See more information about  LESANU, C.-E. on SCOPUS See more information about LESANU, C.-E. on Web of Science, DONE, A. See more information about  DONE, A. on SCOPUS See more information about  DONE, A. on SCOPUS See more information about DONE, A. on Web of Science, COCA, E. See more information about  COCA, E. on SCOPUS See more information about  COCA, E. on SCOPUS See more information about COCA, E. on Web of Science, LAVRIC, A. See more information about LAVRIC, A. on SCOPUS See more information about LAVRIC, A. on SCOPUS See more information about LAVRIC, A. on Web of Science
 
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Download PDF pdficon (1,632 KB) | Citation | Downloads: 24 | Views: 37

Author keywords
computer simulation, intelligent transportation systems, machine learning, routing protocols, vehicular ad hoc networks.

References keywords
satellite(11), learning(11), systems(9), antenna(9), radio(8), internet(7), access(7), communications(6), communication(6), array(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2024-11-30
Volume 24, Issue 4, Year 2024, On page(s): 57 - 64
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2024.04006

Abstract
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This article explores how phased antenna arrays can enhance Low Earth Orbit (LEO) satellite reception systems, while addressing cybersecurity challenges in wireless communications. A conceptual design is proposed to tackle the variable dynamics of LEO satellites and meet the increasing demands of satellite communication systems for future wireless applications. The study highlights the advantages of this approach over traditional beamsteering methods. Integrating advanced artificial intelligence (AI), digital signal processing (DSP), and software-defined radio (SDR) is identified as a transformative strategy, improving adaptability and optimization for phased antenna arrays, particularly in mitigating RF threats. Beamforming evaluations demonstrate how adjusting the phases and amplitudes of feeding signals significantly impacts radiation patterns, enhancing the quality of received signals. The paper's main contribution lies in its comprehensive analysis of key challenges in LEO satellite communications, emphasizing the role of phased antenna arrays alongside AI and SDR. As cyber threats rise, the findings underscore the urgent need for further research into RF protection to secure communication systems in the rapidly evolving landscape of IoT and satellite technologies.


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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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