Paper published in a book (Scientific congresses, symposiums and conference proceedings)
Convolutional Autoencoders for Non-Geostationary Satellite Interference Detection
SAIFALDAWLA AWAD HASSAN, Almoatssimbillah; ORTIZ GOMEZ, Flor de Guadalupe; LAGUNAS, Eva et al.
2024In IEEE International Conference on Communications (IEEE ICC)
Peer reviewed Dataset
 

Files


Full Text
Moatssim__ICC__Final.pdf
Author preprint (1.04 MB)
Download

All documents in ORBilu are protected by a user license.

Send to



Details



Keywords :
GSOs; NGSOs; Interference Detection; Satellite Communication; Convolutional Autoencoders (CAEs)
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SIGCOM - Signal Processing & Communications
Disciplines :
Computer science
Author, co-author :
SAIFALDAWLA AWAD HASSAN, Almoatssimbillah  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
ORTIZ GOMEZ, Flor de Guadalupe  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
LAGUNAS, Eva  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
CHATZINOTAS, Symeon  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
External co-authors :
no
Language :
English
Title :
Convolutional Autoencoders for Non-Geostationary Satellite Interference Detection
Publication date :
12 August 2024
Event name :
IEEE International Conference on Communications (IEEE ICC)
Event organizer :
IEEE
Event place :
Denver, United States - Colorado
Event date :
9-13 June 2024
Audience :
International
Main work title :
IEEE International Conference on Communications (IEEE ICC)
Publisher :
IEEE
Pages :
1334-1339
Peer reviewed :
Peer reviewed
FnR Project :
FNR16193290 - Leveraging Artificial Intelligence To Empower The Next Generation Of Satellite Communications, 2021 (01/09/2022-31/08/2025) - Eva Lagunas
Funders :
FNR - Luxembourg National Research Fund
Funding text :
This work is financially supported by the Luxembourg National Research Fund (FNR) under the project SmartSpace (C21/IS/16193290)
Available on ORBilu :
since 19 March 2024

Statistics


Number of views
118 (48 by Unilu)
Number of downloads
125 (22 by Unilu)

OpenCitations
 
0
OpenAlex citations
 
0

Bibliography


Similar publications



Contact ORBilu