Secrecy Performance Analysis of Integrated RF-UOWC IoT Networks Enabled by UAV and Underwater RIS

In the sixth-generation (6G) Internet of Things (IoT) networks, unmanned aerial vehicle (UAV)-mounted base stations and reconfigurable intelligent surfaces (RISs) have been considered key technologies to enhance coverage, flexibility, and security in nonterrestrial networks (NTNs). In addition to aerial networks enabled by NTN technologies, the integration of underwater networks with 6G IoT can be considered one of the most innovative challenges in future IoT. Along with such trends in IoT, this study investigates the secrecy performance of IoT networks that integrate radio frequency (RF) UAV-based NTNs and underwater optical wireless communication (UOWC) with RISs. Under three potential eavesdropping scenarios, i.e., overhearing of RF signal, UOWC signal, and both signals, we derive closed-form expressions for secrecy performance metrics, including average secrecy capacity, secrecy outage probability, probability of strictly positive secrecy capacity, and effective secrecy throughput. Extensive numerical analyses and Monte Carlo simulations elucidate the impact of system parameters, such as fading severity, the number of RIS reflecting elements, underwater turbulence, pointing errors, and detection techniques on system security. The findings offer comprehensive design guidelines for network deployment aiming to enhance secrecy performance and ensure secure communication in diverse and challenging environments.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-09-27
DOI
https://doi.org/10.1109/jiot.2024.3469731
Citations
12
Primary Topic
Underwater Vehicles and Communication Systems
Type
article
Field-Weighted Citation Impact
4.03
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article

Secrecy Performance Analysis of Integrated RF-UOWC IoT Networks Enabled by UAV and Underwater RIS

Md. Ibrahim, Imran Shafique Ansari, A. S. M. Badrudduza, Heejung Yu et al.
12 citations
IEEE Internet of Things Journal
Underwater Vehicles and Communication Systems
4.03
article

Secrecy Performance Analysis of Integrated RF-UOWC IoT Networks Enabled by UAV and Underwater RIS

Md. Ibrahim, Imran Shafique Ansari, A. S. M. Badrudduza, Heejung Yu, Abrar Bin Sarawar
article en
12 citations

Abstract

In the sixth-generation (6G) Internet of Things (IoT) networks, unmanned aerial vehicle (UAV)-mounted base stations and reconfigurable intelligent surfaces (RISs) have been considered key technologies to enhance coverage, flexibility, and security in nonterrestrial networks (NTNs). In addition to aerial networks enabled by NTN technologies, the integration of underwater networks with 6G IoT can be considered one of the most innovative challenges in future IoT. Along with such trends in IoT, this study investigates the secrecy performance of IoT networks that integrate radio frequency (RF) UAV-based NTNs and underwater optical wireless communication (UOWC) with RISs. Under three potential eavesdropping scenarios, i.e., overhearing of RF signal, UOWC signal, and both signals, we derive closed-form expressions for secrecy performance metrics, including average secrecy capacity, secrecy outage probability, probability of strictly positive secrecy capacity, and effective secrecy throughput. Extensive numerical analyses and Monte Carlo simulations elucidate the impact of system parameters, such as fading severity, the number of RIS reflecting elements, underwater turbulence, pointing errors, and detection techniques on system security. The findings offer comprehensive design guidelines for network deployment aiming to enhance secrecy performance and ensure secure communication in diverse and challenging environments.

IEEE Internet of Things JournalVol. 12(3)
Rajshahi University of Engineering and Technology (BD), Korea University (KR), Rajshahi University of Engineering and Technology (BD), University of Glasgow (GB)
Openalex Percentile: Top 6%
Underwater Vehicles and Communication Systems
4.03
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Secrecy Performance Analysis of Integrated RF-UOWC IoT Networks Enabled by UAV and Underwater RIS — Md. Ibrahim, Imran Shafique Ansari, et al. · IEEE Internet of Things Journal (2024) | TGRS Research Map | TGRS