cooperative relay; Deep learning; friendly jamming; physical layer security; satellite communications; Analytical approach; Cooperative relay; Friendly jamming; Jammers; Learning approach; Outage probability; Physical layer security; Satellite communications; Secrecy outage probabilities; Control and Systems Engineering; Information Systems; Computer Science Applications; Computer Networks and Communications; Electrical and Electronic Engineering; Relays; Jamming; Eavesdropping; Satellites; Satellite broadcasting; Probability density function; Power system reliability; Communication system security; Urban areas; Space-air-ground integrated networks
Abstract :
[en] This article introduces novel and deep learning approaches for the security analysis of a hybrid satellite-terrestrial cooperative network. More specifically, a satellite transmits information to a ground user through multiple relays in the presence of an eavesdropper. To prevent potential eavesdropping, multiple friendly jammers are employed to disrupt the reception process of the eavesdropper by artificial noise. Within this setting, we then derive the closed-form expressions of the outage probability (OP) and secrecy outage probability (SOP) of the considered system in the presence of imperfect channel state information. Important to mention is the fact that in complex systems (e.g., with multiple jammers, multiple relays, and considering the independent but nonidentically distributed Rician nature of satellite links), analytical approaches may not be effective due to their complex mathematical derivations. As such, we develop a highly effective yet low-complexity deep learning approach to estimate the OP and SOP of the system. Through extensive Monte Carlo simulations, we evaluate the OP and SOP of the system in various settings and demonstrate the effectiveness of the proposed solutions. Interestingly, the proposed deep learning method can achieve comparable performance to that of the analytical approach.
Disciplines :
Computer science
Author, co-author :
Nguyen, Tan N. ; Ton Duc Thang University, Communication and Signal Processing Research Group, Faculty of Electrical and Electronics Engineering, Ho Chi Minh City, Viet Nam
Van Chien, Trinh ; Hanoi University of Science and Technology, School of Information and Communication Technology (SoICT), Ha Noi, Viet Nam
TRAN DINH, Hieu ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
Miroslav, Voznak; the VSB - Technical University of Ostrava, 708 33 Ostrava - Poruba, Czech Republic
Zhiguo, Ding; The University of Manchester, Manchester, M13 9PL, UK
External co-authors :
yes
Language :
English
Title :
Cooperative Satellite-Terrestrial Networks With Imperfect CSI and Multiple Jammers: Performance Analysis and Deep Learning Evaluation
Alternative titles :
[en] Cooperative Satellite-Terrestrial Networks With Imperfect CSI and Multiple Jammers: Performance Analysis and Deep Learning Evaluation
Original title :
[en] Cooperative Satellite-Terrestrial Networks With Imperfect CSI and Multiple Jammers: Performance Analysis and Deep Learning Evaluation
Publication date :
01 October 2024
Journal title :
IEEE Systems Journal
ISSN :
1932-8184
eISSN :
1937-9234
Publisher :
Institute of Electrical and Electronics Engineers Inc.
European Commission European Just Transition Fund Ministry of Education, Youth and Sports of the Czech Republic Technical University of Ostrava
Funding text :
Received 5 January 2024; revised 26 April 2024 and 22 July 2024; accepted 7 September 2024. This work was supported in part by the European Union within the REFRESH project - Research Excellence For Region Sustainability and High-tech Industries under Grant CZ.10.03.01/00/22_003/0000048, in part by the European Just Transition Fund and by the Ministry of Education, Youth and Sports of the Czech Republic (MEYS CZ) under Grant SP 061/2024 conducted by VSB - Technical University of Ostrava. (Corresponding author: Bui Vu Minh.) Tan N. Nguyen is with the Communication and Signal Processing Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City 70000, Vietnam (e-mail: nguyennhat-tan@tdtu.edu.vn).
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