Channel estimation for reconfigurable intelligent surface-aided millimeter-wave massive multiple-input multiple-output system with deep residual attention network
We first model the channel estimation in sixth-generation (6G) systems as a super-resolution problem and adopt a deep residual attention approach to learn the nontrivial mapping from the received measurement to the reconfi-gurable intelligent surface (RIS) channel. Subsequently, we design a deep res...
Saved in:
Main Authors: | Xuhui Zheng, Ziyan Liu, Shitong Cheng, Yingyu Wu, Yunlei Chen, Qian Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
Electronics and Telecommunications Research Institute (ETRI)
2025-06-01
|
Series: | ETRI Journal |
Subjects: | |
Online Access: | https://doi.org/10.4218/etrij.2023-0555 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Super-Resolution Reconstruction Method of Face Image Based on Attention Mechanism
by: Chenglin Yu, et al.
Published: (2025-01-01) -
Tunable and Reconfigurable Dual-Band Chiral Metamirror
by: Junxing Fan, et al.
Published: (2020-01-01) -
Compressive Super-Resolution Imaging Based on Scrambled Block Hadamard Ensemble
by: Yicheng Sun, et al.
Published: (2016-01-01) -
Reconfigurable RF Filter Based on Cascaded Microring Resonators
by: Ziyang Lu, et al.
Published: (2023-01-01) -
RECONFIGURATION OF THE AIRCRAFT INTEGRATED CONTROL SYSTEM REGARDING CONTROL CONSTRAINTS UNDER ACTUATOR FAILURES
by: A. M. Kulchak, et al.
Published: (2018-12-01)