Yu, Y.; Wang, J.; Zhou, X.; Wang, C.; Bai, Z.; Ye, Z. Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication System. Mathematics2023, 11, 3235.
Yu, Y.; Wang, J.; Zhou, X.; Wang, C.; Bai, Z.; Ye, Z. Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication System. Mathematics 2023, 11, 3235.
Yu, Y.; Wang, J.; Zhou, X.; Wang, C.; Bai, Z.; Ye, Z. Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication System. Mathematics2023, 11, 3235.
Yu, Y.; Wang, J.; Zhou, X.; Wang, C.; Bai, Z.; Ye, Z. Review on Channel Estimation for Reconfigurable Intelligent Surface Assisted Wireless Communication System. Mathematics 2023, 11, 3235.
Abstract
With the dramatic increase in the number of mobile users and wireless devices accessing the network, the performance of the fifth generation (5G) wireless communication systems has been severely challenged. Reconfigurable intelligent surfaces (RIS), one of the potential technologies for the sixth generation (6G), has received a lot of attention. Since it is easier to deploy, consumes less power, and is inexpensive. 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 paper conducts a comprehensive investigation of the existing channel estimation methods of RIS, analysis and comparison of channel model building and CSI acquisition schemes in different frequency bands, in addition to a comprehensive description of generic channel estimation methods, with a focus on the application of deep learning. Finally, we conclude the paper and provide an outlook in the future development of RIS channel estimation.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
