Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication System
With the dramatic increase in the number of mobile users and wireless devices accessing the network, the performance of fifth generation (5G) wireless communication systems has been severely challenged. Reconfigurable intelligent surface (RIS) has received much attention as one of the promising tech...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/14/3235 |
| _version_ | 1797588450760720384 |
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| author | Yun Yu Jinhao Wang Xiao Zhou Chengyou Wang Zhiquan Bai Zhun Ye |
| author_facet | Yun Yu Jinhao Wang Xiao Zhou Chengyou Wang Zhiquan Bai Zhun Ye |
| author_sort | Yun Yu |
| collection | DOAJ |
| description | With the dramatic increase in the number of mobile users and wireless devices accessing the network, the performance of fifth generation (5G) wireless communication systems has been severely challenged. Reconfigurable intelligent surface (RIS) has received much attention as one of the promising technologies for the sixth generation (6G) due to its ease of deployment, low power consumption, and low price. RIS is an electromagnetic metamaterial that serves to reconfigure the wireless environment by adjusting the phase, amplitude, and frequency of the wireless signal. To maximize channel transmission efficiency and improve the reliability of communication systems, the acquisition of channel state information (CSI) is essential. Therefore, an effective channel estimation method guarantees the achievement of excellent RIS performance. This survey presents a comprehensive study of existing channel estimation methods for RIS. Firstly, channel estimation methods in high and low frequency bands are overviewed and compared. We focus on channel estimation in the high frequency band and analyze the system model. Then, the comprehensive description of the different channel estimation methods is given, with a focus on the application of deep learning. Finally, we conclude the paper and provide an outlook on the future development of RIS channel estimation. |
| first_indexed | 2024-03-11T00:52:10Z |
| format | Article |
| id | doaj.art-d7398a326927400ab5092dbc0b80e8ad |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T00:52:10Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-d7398a326927400ab5092dbc0b80e8ad2023-11-18T20:22:35ZengMDPI AGMathematics2227-73902023-07-011114323510.3390/math11143235Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication SystemYun Yu0Jinhao Wang1Xiao Zhou2Chengyou Wang3Zhiquan Bai4Zhun Ye5School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai 264209, ChinaSchool of Mechanical, Electrical and Information Engineering, Shandong University, Weihai 264209, ChinaSchool of Mechanical, Electrical and Information Engineering, Shandong University, Weihai 264209, ChinaSchool of Mechanical, Electrical and Information Engineering, Shandong University, Weihai 264209, ChinaSchool of Information Science and Engineering, Shandong University, Qingdao 266237, ChinaSchool of Mechanical, Electrical and Information Engineering, Shandong University, Weihai 264209, ChinaWith the dramatic increase in the number of mobile users and wireless devices accessing the network, the performance of fifth generation (5G) wireless communication systems has been severely challenged. Reconfigurable intelligent surface (RIS) has received much attention as one of the promising technologies for the sixth generation (6G) due to its ease of deployment, low power consumption, and low price. RIS is an electromagnetic metamaterial that serves to reconfigure the wireless environment by adjusting the phase, amplitude, and frequency of the wireless signal. To maximize channel transmission efficiency and improve the reliability of communication systems, the acquisition of channel state information (CSI) is essential. Therefore, an effective channel estimation method guarantees the achievement of excellent RIS performance. This survey presents a comprehensive study of existing channel estimation methods for RIS. Firstly, channel estimation methods in high and low frequency bands are overviewed and compared. We focus on channel estimation in the high frequency band and analyze the system model. Then, the comprehensive description of the different channel estimation methods is given, with a focus on the application of deep learning. Finally, we conclude the paper and provide an outlook on the future development of RIS channel estimation.https://www.mdpi.com/2227-7390/11/14/3235wireless communication systemsixth generation (6G)reconfigurable intelligent surface (RIS)channel estimation |
| spellingShingle | Yun Yu Jinhao Wang Xiao Zhou Chengyou Wang Zhiquan Bai Zhun Ye Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication System Mathematics wireless communication system sixth generation (6G) reconfigurable intelligent surface (RIS) channel estimation |
| title | Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication System |
| title_full | Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication System |
| title_fullStr | Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication System |
| title_full_unstemmed | Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication System |
| title_short | Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication System |
| title_sort | review on channel estimation for reconfigurable intelligent surface assisted wireless communication system |
| topic | wireless communication system sixth generation (6G) reconfigurable intelligent surface (RIS) channel estimation |
| url | https://www.mdpi.com/2227-7390/11/14/3235 |
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