DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications

<p dir="ltr">This paper explores a new advancement in physical layer security (PLS) techniques, focusing on the integration of Intelligent Reflecting Surfaces (IRS). This work centers on developing an intelligent hybrid system combining communication lines using millimeter wave (mmWa...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Danya A. Saifaldeen (19498705) (author)
مؤلفون آخرون: Abdullatif M. Al-Baseer (21248960) (author), Bekir S. Ciftler (16904883) (author), Mohamed M. Abdallah (8476953) (author), Khalid A. Qaraqe (16904664) (author)
منشور في: 2024
الموضوعات:
الوسوم: إضافة وسم
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author Danya A. Saifaldeen (19498705)
author2 Abdullatif M. Al-Baseer (21248960)
Bekir S. Ciftler (16904883)
Mohamed M. Abdallah (8476953)
Khalid A. Qaraqe (16904664)
author2_role author
author
author
author
author_facet Danya A. Saifaldeen (19498705)
Abdullatif M. Al-Baseer (21248960)
Bekir S. Ciftler (16904883)
Mohamed M. Abdallah (8476953)
Khalid A. Qaraqe (16904664)
author_role author
dc.creator.none.fl_str_mv Danya A. Saifaldeen (19498705)
Abdullatif M. Al-Baseer (21248960)
Bekir S. Ciftler (16904883)
Mohamed M. Abdallah (8476953)
Khalid A. Qaraqe (16904664)
dc.date.none.fl_str_mv 2024-04-30T09:00:00Z
dc.identifier.none.fl_str_mv 10.1109/ojcoms.2024.3395425
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/DRL-Based_IRS-Assisted_Secure_Hybrid_Visible_Light_and_mmWave_Communications/28935950
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Engineering
Communications engineering
Electrical engineering
Information and computing sciences
Artificial intelligence
Machine learning
visible light communications
millimeter wave
deep learning
machine learning
deep reinforcement learning
intelligent reflecting surfaces
secrecy capacity
physical layer security
deep deterministic policy gradient
dc.title.none.fl_str_mv DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">This paper explores a new advancement in physical layer security (PLS) techniques, focusing on the integration of Intelligent Reflecting Surfaces (IRS). This work centers on developing an intelligent hybrid system combining communication lines using millimeter wave (mmWave) and Visible light communication (VLC). The system comprises four VLC access points with light fixtures, reinforced by a mirror array sheet, and a mmWave access point with antennas, supported by a reflecting unit sheet. Within the system, both sheets function as IRS. The aim is to enhance the secrecy capacity (SC) of the system by optimizing the beamforming weights at the VLC fixtures, the beamforming weights at the mmWave AP, the mirror array configurations, and the phase shift vector while meeting specific power constraints. Given the numerous variables and the dynamic nature of user mobility, traditional optimization techniques may be inadequate for improving SC. To address this complexity optimally, we propose a deep reinforcement learning (DRL) approach based on the deep deterministic policy gradient (DDPG) technique. The DDPG algorithm can adapt to channel variations due to user movement and high-dimensional factors. Furthermore, it intelligently selects the optimal technique to improve SC, whether VLC or RF. Simulation results confirm the efficacy of our approach in enhancing the SC for the authorized receiver, particularly in mmWave connections.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Open Journal of the Communications Society<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/ojcoms.2024.3395425" target="_blank">https://dx.doi.org/10.1109/ojcoms.2024.3395425</a></p><p><br></p>
eu_rights_str_mv openAccess
id Manara2_0bdef11b0276a6eccdc1b9da2c9605d5
identifier_str_mv 10.1109/ojcoms.2024.3395425
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/28935950
publishDate 2024
repository.mail.fl_str_mv
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rights_invalid_str_mv CC BY 4.0
spelling DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave CommunicationsDanya A. Saifaldeen (19498705)Abdullatif M. Al-Baseer (21248960)Bekir S. Ciftler (16904883)Mohamed M. Abdallah (8476953)Khalid A. Qaraqe (16904664)EngineeringCommunications engineeringElectrical engineeringInformation and computing sciencesArtificial intelligenceMachine learningvisible light communicationsmillimeter wavedeep learningmachine learningdeep reinforcement learningintelligent reflecting surfacessecrecy capacityphysical layer securitydeep deterministic policy gradient<p dir="ltr">This paper explores a new advancement in physical layer security (PLS) techniques, focusing on the integration of Intelligent Reflecting Surfaces (IRS). This work centers on developing an intelligent hybrid system combining communication lines using millimeter wave (mmWave) and Visible light communication (VLC). The system comprises four VLC access points with light fixtures, reinforced by a mirror array sheet, and a mmWave access point with antennas, supported by a reflecting unit sheet. Within the system, both sheets function as IRS. The aim is to enhance the secrecy capacity (SC) of the system by optimizing the beamforming weights at the VLC fixtures, the beamforming weights at the mmWave AP, the mirror array configurations, and the phase shift vector while meeting specific power constraints. Given the numerous variables and the dynamic nature of user mobility, traditional optimization techniques may be inadequate for improving SC. To address this complexity optimally, we propose a deep reinforcement learning (DRL) approach based on the deep deterministic policy gradient (DDPG) technique. The DDPG algorithm can adapt to channel variations due to user movement and high-dimensional factors. Furthermore, it intelligently selects the optimal technique to improve SC, whether VLC or RF. Simulation results confirm the efficacy of our approach in enhancing the SC for the authorized receiver, particularly in mmWave connections.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Open Journal of the Communications Society<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/ojcoms.2024.3395425" target="_blank">https://dx.doi.org/10.1109/ojcoms.2024.3395425</a></p><p><br></p>2024-04-30T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/ojcoms.2024.3395425https://figshare.com/articles/journal_contribution/DRL-Based_IRS-Assisted_Secure_Hybrid_Visible_Light_and_mmWave_Communications/28935950CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/289359502024-04-30T09:00:00Z
spellingShingle DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
Danya A. Saifaldeen (19498705)
Engineering
Communications engineering
Electrical engineering
Information and computing sciences
Artificial intelligence
Machine learning
visible light communications
millimeter wave
deep learning
machine learning
deep reinforcement learning
intelligent reflecting surfaces
secrecy capacity
physical layer security
deep deterministic policy gradient
status_str publishedVersion
title DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
title_full DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
title_fullStr DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
title_full_unstemmed DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
title_short DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
title_sort DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
topic Engineering
Communications engineering
Electrical engineering
Information and computing sciences
Artificial intelligence
Machine learning
visible light communications
millimeter wave
deep learning
machine learning
deep reinforcement learning
intelligent reflecting surfaces
secrecy capacity
physical layer security
deep deterministic policy gradient