Secure Satellite Downlink With Hybrid RIS and AI-Based Optimization
In this paper, we explore a secure multiuser multiple-input single-output (MISO) satellite downlink communication system, enhanced by the integration of a hybrid reconfigurable intelligent surface (RIS). The study formulates a robust joint design for satellite and RIS beamforming, aimed at maximizin...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10810415/ |
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| author | Mian Muhammad Kamal Syed Zain Ul Abideen Syed Sikandar Shah Nabila Sehito Salahuddin Khan Bal S. Virdee Mohammad Alibakhshikenari Patrizia Livreri |
| author_facet | Mian Muhammad Kamal Syed Zain Ul Abideen Syed Sikandar Shah Nabila Sehito Salahuddin Khan Bal S. Virdee Mohammad Alibakhshikenari Patrizia Livreri |
| author_sort | Mian Muhammad Kamal |
| collection | DOAJ |
| description | In this paper, we explore a secure multiuser multiple-input single-output (MISO) satellite downlink communication system, enhanced by the integration of a hybrid reconfigurable intelligent surface (RIS). The study formulates a robust joint design for satellite and RIS beamforming, aimed at maximizing the secrecy rate of the overall system. Both the active and passive elements of the RIS are optimized, taking into account practical models that reflect real-world constraints, such as outdated channel state information (CSI) and the power consumption of the system. To address the highly complex, dynamic, and multidimensional nature of the beamforming design problem, deep reinforcement learning (DRL) techniques are employed. Simulation results demonstrate the effectiveness of the proposed beamforming strategy, highlighting significant performance improvements when utilizing hybrid-RIS compared to traditional passive RIS solutions in wireless communication systems. |
| format | Article |
| id | doaj-art-b7efbab3a1e44a86822f102df8e59164 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-b7efbab3a1e44a86822f102df8e591642025-01-21T00:01:23ZengIEEEIEEE Access2169-35362025-01-01133726373710.1109/ACCESS.2024.352079610810415Secure Satellite Downlink With Hybrid RIS and AI-Based OptimizationMian Muhammad Kamal0https://orcid.org/0000-0002-0159-9655Syed Zain Ul Abideen1https://orcid.org/0009-0008-3740-2472Syed Sikandar Shah2https://orcid.org/0000-0002-6082-3418Nabila Sehito3Salahuddin Khan4Bal S. Virdee5https://orcid.org/0000-0001-7203-0039Mohammad Alibakhshikenari6https://orcid.org/0000-0002-8263-1572Patrizia Livreri7https://orcid.org/0000-0001-8599-0418School of Electronic Science and Engineering, Southeast University, Jiangning, Nanjing, Jiangsu, ChinaCollege of Computer Science and Technology, Qingdao University, Qingdao, ChinaSchool of Optical Electrical and Computer Science Engineering, University of Shanghai Science and Technology (USST), Shanghai, ChinaDepartment of Computer Science, Ilma University, Karachi, PakistanCollege of Engineering, King Saud University, Riyadh, Saudi ArabiaCenter for Communications Technology, London Metropolitan University, London, U.K.Electronics Engineering Department, University of Rome “Tor Vergata,”, Rome, ItalyDepartment of Engineering, University of Palermo, Palermo, Sicily, ItalyIn this paper, we explore a secure multiuser multiple-input single-output (MISO) satellite downlink communication system, enhanced by the integration of a hybrid reconfigurable intelligent surface (RIS). The study formulates a robust joint design for satellite and RIS beamforming, aimed at maximizing the secrecy rate of the overall system. Both the active and passive elements of the RIS are optimized, taking into account practical models that reflect real-world constraints, such as outdated channel state information (CSI) and the power consumption of the system. To address the highly complex, dynamic, and multidimensional nature of the beamforming design problem, deep reinforcement learning (DRL) techniques are employed. Simulation results demonstrate the effectiveness of the proposed beamforming strategy, highlighting significant performance improvements when utilizing hybrid-RIS compared to traditional passive RIS solutions in wireless communication systems.https://ieeexplore.ieee.org/document/10810415/Hybrid reconfigurable intelligent surface (RIS)deep reinforcement learning (DRL)active and passive RIS elementsphysical layer security (PLS) |
| spellingShingle | Mian Muhammad Kamal Syed Zain Ul Abideen Syed Sikandar Shah Nabila Sehito Salahuddin Khan Bal S. Virdee Mohammad Alibakhshikenari Patrizia Livreri Secure Satellite Downlink With Hybrid RIS and AI-Based Optimization IEEE Access Hybrid reconfigurable intelligent surface (RIS) deep reinforcement learning (DRL) active and passive RIS elements physical layer security (PLS) |
| title | Secure Satellite Downlink With Hybrid RIS and AI-Based Optimization |
| title_full | Secure Satellite Downlink With Hybrid RIS and AI-Based Optimization |
| title_fullStr | Secure Satellite Downlink With Hybrid RIS and AI-Based Optimization |
| title_full_unstemmed | Secure Satellite Downlink With Hybrid RIS and AI-Based Optimization |
| title_short | Secure Satellite Downlink With Hybrid RIS and AI-Based Optimization |
| title_sort | secure satellite downlink with hybrid ris and ai based optimization |
| topic | Hybrid reconfigurable intelligent surface (RIS) deep reinforcement learning (DRL) active and passive RIS elements physical layer security (PLS) |
| url | https://ieeexplore.ieee.org/document/10810415/ |
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