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Aerial RIS-Aided Physical Layer Security: Optimal Deployment and Partitioning

delete2024-10-01
delete6
PRE
AI
S
Sultangali Arzykulov *
A
Abdulkadir Çelik
G
Galymzhan Nauryzbayev
A
Ahmed M. Eltawil
DOI:10.1109/TCCN.2024.3392798delete
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摘要

摘要

En 中文
We propose a novel approach for enhancing physical layer security (PLS) in wireless networks by utilizing a combination of reconfigurable intelligent surfaces (RIS) and artificial noise (AN). The proposed aerial RIS (A-RIS) concept utilizes a RIS-attached unmanned aerial vehicle (UAV) that hovers over the network area to improve the signal quality for legitimate users and jam that of illegitimate ones. We propose a method of virtually partitioning the RIS, such that the partition phase shifts are configured to improve the intended signal at a legitimate user while simultaneously increasing the impact of AN on illegitimate users. Closed-form (CF) expressions for legitimate and illegitimate users' ergodic secrecy capacity (ESC) are derived and validated. Then, optimization problems are formulated to maximize network ESC by optimizing the 3D deployment of the A-RIS and RIS portions for users subject to predefined quality-of-service constraints. Simulation results validate CF solutions and demonstrate that the proposed joint A-RIS deployment and partitioning framework can significantly improve network security compared to benchmarks where RIS and AN are separately used without deployment optimization. Additionally, the proposed deployment approaches converge in less than a second using CF optimal RIS portions, making it suitable for dynamic A-RIS deployment.
Keyword:
Reconfigurable intelligent surfaces
Autonomous aerial vehicles
Optimization
Array signal processing
Wireless networks
Three-dimensional displays
Energy efficiency
Artificial noise (AN)
ergodic secrecy capacity (ESC)
physical layer security (PLS)
optimization
partitioning
power control
unmanned aerial vehicle (UAV)
reconfigurable intelligent surface (RIS)

期刊

I
IEEE Transactions on Cognitive Communications and Networking
IF:
7
论文数:
1.5K
被引数:
5.5K

机构

K
king abdullah university of science & technology
学者数:
1.3W
论文数: 1.3W
被引数: 32
N
Nazarbayev University
学者数:
4.7K
论文数: 3.1K
被引数: 3.1K
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