Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review
An intelligent reflecting surface (IRS) is a programmable device that can be used to control electromagnetic waves propagation by changing the electric and magnetic properties of its surface. Therefore, IRS is considered a smart technology for the sixth generation (6G) of communication networks. In...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/14/5405 |
| _version_ | 1797433104002973696 |
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| author | Mohammad Abrar Shakil Sejan Md Habibur Rahman Beom-Sik Shin Ji-Hye Oh Young-Hwan You Hyoung-Kyu Song |
| author_facet | Mohammad Abrar Shakil Sejan Md Habibur Rahman Beom-Sik Shin Ji-Hye Oh Young-Hwan You Hyoung-Kyu Song |
| author_sort | Mohammad Abrar Shakil Sejan |
| collection | DOAJ |
| description | An intelligent reflecting surface (IRS) is a programmable device that can be used to control electromagnetic waves propagation by changing the electric and magnetic properties of its surface. Therefore, IRS is considered a smart technology for the sixth generation (6G) of communication networks. In addition, machine learning (ML) techniques are now widely adopted in wireless communication as the computation power of devices has increased. As it is an emerging topic, we provide a comprehensive overview of the state-of-the-art on ML, especially on deep learning (DL)-based IRS-enhanced communication. We focus on their operating principles, channel estimation (CE), and the applications of machine learning to IRS-enhanced wireless networks. In addition, we systematically survey existing designs for IRS-enhanced wireless networks. Furthermore, we identify major issues and research opportunities associated with the integration of IRS and other emerging technologies for applications to next-generation wireless communication. |
| first_indexed | 2024-03-09T10:12:22Z |
| format | Article |
| id | doaj.art-43e73f6c26a44f69a46e92f9202f1320 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T10:12:22Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-43e73f6c26a44f69a46e92f9202f13202023-12-01T22:40:57ZengMDPI AGSensors1424-82202022-07-012214540510.3390/s22145405Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A ReviewMohammad Abrar Shakil Sejan0Md Habibur Rahman1Beom-Sik Shin2Ji-Hye Oh3Young-Hwan You4Hyoung-Kyu Song5Department of Information and Communication Engineering, Sejong University, Seoul 05006, KoreaDepartment of Information and Communication Engineering, Sejong University, Seoul 05006, KoreaDepartment of Information and Communication Engineering, Sejong University, Seoul 05006, KoreaDepartment of Information and Communication Engineering, Sejong University, Seoul 05006, KoreaDepartment of Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, KoreaDepartment of Information and Communication Engineering, Sejong University, Seoul 05006, KoreaAn intelligent reflecting surface (IRS) is a programmable device that can be used to control electromagnetic waves propagation by changing the electric and magnetic properties of its surface. Therefore, IRS is considered a smart technology for the sixth generation (6G) of communication networks. In addition, machine learning (ML) techniques are now widely adopted in wireless communication as the computation power of devices has increased. As it is an emerging topic, we provide a comprehensive overview of the state-of-the-art on ML, especially on deep learning (DL)-based IRS-enhanced communication. We focus on their operating principles, channel estimation (CE), and the applications of machine learning to IRS-enhanced wireless networks. In addition, we systematically survey existing designs for IRS-enhanced wireless networks. Furthermore, we identify major issues and research opportunities associated with the integration of IRS and other emerging technologies for applications to next-generation wireless communication.https://www.mdpi.com/1424-8220/22/14/5405intelligent reflecting surfaces (IRSs)machine learningmultiple input multiple outputwireless networks |
| spellingShingle | Mohammad Abrar Shakil Sejan Md Habibur Rahman Beom-Sik Shin Ji-Hye Oh Young-Hwan You Hyoung-Kyu Song Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review Sensors intelligent reflecting surfaces (IRSs) machine learning multiple input multiple output wireless networks |
| title | Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review |
| title_full | Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review |
| title_fullStr | Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review |
| title_full_unstemmed | Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review |
| title_short | Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review |
| title_sort | machine learning for intelligent reflecting surface based wireless communication towards 6g a review |
| topic | intelligent reflecting surfaces (IRSs) machine learning multiple input multiple output wireless networks |
| url | https://www.mdpi.com/1424-8220/22/14/5405 |
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