PPO-based deployment and phase control for movable intelligent reflecting surface
Abstract Intelligent reflecting surface (IRS) stands as a promising technology to revolutionize wireless communication by manipulating incident signal amplitudes and phases to enhance system performance. While existing research primarily centers around optimizing the phase shifts of IRS, the deploym...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-12-01
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| Series: | Journal of Cloud Computing: Advances, Systems and Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13677-023-00528-1 |
| _version_ | 1797413997589299200 |
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| author | Yikun Zhao Fanqin Zhou Huaide Liu Lei Feng Wenjing Li |
| author_facet | Yikun Zhao Fanqin Zhou Huaide Liu Lei Feng Wenjing Li |
| author_sort | Yikun Zhao |
| collection | DOAJ |
| description | Abstract Intelligent reflecting surface (IRS) stands as a promising technology to revolutionize wireless communication by manipulating incident signal amplitudes and phases to enhance system performance. While existing research primarily centers around optimizing the phase shifts of IRS, the deployment of IRS on movable platforms introduces a new degree of freedom in the design of IRS-assisted systems. Leveraging flexible deployment strategies for IRS holds the potential to further amplify network throughput and extend coverage. This paper addresses the challenging non-convex joint optimization problem of the movable IRS and proposes a dynamic optimization algorithm based on proximal policy optimization (PPO) for dynamically optimizing the aerial position and phase configuration of IRS. Simulation results show the effectiveness of the proposed approach, demonstrating significant performance improvements compared to communication schemes without IRS assistance and conventional static IRS-assisted methods. |
| first_indexed | 2024-03-09T05:26:37Z |
| format | Article |
| id | doaj.art-bbc2482fe161413383053b0f8d9ad08c |
| institution | Directory Open Access Journal |
| issn | 2192-113X |
| language | English |
| last_indexed | 2024-03-09T05:26:37Z |
| publishDate | 2023-12-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Cloud Computing: Advances, Systems and Applications |
| spelling | doaj.art-bbc2482fe161413383053b0f8d9ad08c2023-12-03T12:36:31ZengSpringerOpenJournal of Cloud Computing: Advances, Systems and Applications2192-113X2023-12-0112111010.1186/s13677-023-00528-1PPO-based deployment and phase control for movable intelligent reflecting surfaceYikun Zhao0Fanqin Zhou1Huaide Liu2Lei Feng3Wenjing Li4State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and TelecommunicationsState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and TelecommunicationsState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and TelecommunicationsState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and TelecommunicationsState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and TelecommunicationsAbstract Intelligent reflecting surface (IRS) stands as a promising technology to revolutionize wireless communication by manipulating incident signal amplitudes and phases to enhance system performance. While existing research primarily centers around optimizing the phase shifts of IRS, the deployment of IRS on movable platforms introduces a new degree of freedom in the design of IRS-assisted systems. Leveraging flexible deployment strategies for IRS holds the potential to further amplify network throughput and extend coverage. This paper addresses the challenging non-convex joint optimization problem of the movable IRS and proposes a dynamic optimization algorithm based on proximal policy optimization (PPO) for dynamically optimizing the aerial position and phase configuration of IRS. Simulation results show the effectiveness of the proposed approach, demonstrating significant performance improvements compared to communication schemes without IRS assistance and conventional static IRS-assisted methods.https://doi.org/10.1186/s13677-023-00528-1Intelligent reflecting surface (IRS)Deep reinforcement learning (DRL)Movable deployment |
| spellingShingle | Yikun Zhao Fanqin Zhou Huaide Liu Lei Feng Wenjing Li PPO-based deployment and phase control for movable intelligent reflecting surface Journal of Cloud Computing: Advances, Systems and Applications Intelligent reflecting surface (IRS) Deep reinforcement learning (DRL) Movable deployment |
| title | PPO-based deployment and phase control for movable intelligent reflecting surface |
| title_full | PPO-based deployment and phase control for movable intelligent reflecting surface |
| title_fullStr | PPO-based deployment and phase control for movable intelligent reflecting surface |
| title_full_unstemmed | PPO-based deployment and phase control for movable intelligent reflecting surface |
| title_short | PPO-based deployment and phase control for movable intelligent reflecting surface |
| title_sort | ppo based deployment and phase control for movable intelligent reflecting surface |
| topic | Intelligent reflecting surface (IRS) Deep reinforcement learning (DRL) Movable deployment |
| url | https://doi.org/10.1186/s13677-023-00528-1 |
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