RIS-aided AANETs: Security maximization relying on unsupervised projection-based neural networks
RIS-aided AANETs: Security maximization relying on unsupervised projection-based neural networks
The security aspects of aeronautical {\em ad-hoc} networks (AANET) relying on reflective intelligent surface (RIS) are considered. A projection-based deep neural network is designed for maximizing the secrecy rate of the proposed RIS-aided AANET. It is shown that our design outperforms the state-of-the-art projected gradient descent algorithms and that the RIS is capable of enhancing the security.
Aircraft, Fading channels, Neural networks, Optimization, Rician channels, Security, UHF antennas
Hoang, Minh Tiep
79ed4c0b-02ee-420a-a4cf-eeb0c2715d76
Luong, Thien V.
94780ac4-289f-47b6-9923-0c5636b78838
Liu, Dong
a7aff28b-d69f-4e93-bce9-bbe3000f59ef
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
9 December 2021
Hoang, Minh Tiep
79ed4c0b-02ee-420a-a4cf-eeb0c2715d76
Luong, Thien V.
94780ac4-289f-47b6-9923-0c5636b78838
Liu, Dong
a7aff28b-d69f-4e93-bce9-bbe3000f59ef
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Hoang, Minh Tiep, Luong, Thien V., Liu, Dong and Hanzo, Lajos
(2021)
RIS-aided AANETs: Security maximization relying on unsupervised projection-based neural networks.
IEEE Transactions on Vehicular Technology.
(doi:10.1109/TVT.2021.3133947).
Abstract
The security aspects of aeronautical {\em ad-hoc} networks (AANET) relying on reflective intelligent surface (RIS) are considered. A projection-based deep neural network is designed for maximizing the secrecy rate of the proposed RIS-aided AANET. It is shown that our design outperforms the state-of-the-art projected gradient descent algorithms and that the RIS is capable of enhancing the security.
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RIS_IGAS_CAMERA_READY_1_
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RIS-aided AANETs: Security Maximization Relying on Unsupervised Projection-based Neural Networks
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Accepted/In Press date: 6 December 2021
Published date: 9 December 2021
Additional Information:
Publisher Copyright:
IEEE
Keywords:
Aircraft, Fading channels, Neural networks, Optimization, Rician channels, Security, UHF antennas
Identifiers
Local EPrints ID: 453117
URI: http://eprints.soton.ac.uk/id/eprint/453117
ISSN: 0018-9545
PURE UUID: 80f5e914-4287-4a7f-a863-ccf78d1dc8de
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Date deposited: 08 Jan 2022 22:20
Last modified: 18 Mar 2024 02:36
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Contributors
Author:
Minh Tiep Hoang
Author:
Thien V. Luong
Author:
Dong Liu
Author:
Lajos Hanzo
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