Deep learning for compressed sensing based sparse channel estimation in FDD massive MIMO systems
For FDD massive multi-input multi-output (MIMO) downlink system, a novel deep learning method for compressed sensing based sparse channel estimation was proposed, which was called convolutional compressed sensing network (ConCSNet).In the ConCSNet, the convolutional neural network was utilized to so...
Saved in:
Main Authors: | Yuan HUANG, Yigang HE, Yuting WU, Tongtong CHENG, Yongbo SUI, Shuguang NING |
---|---|
Format: | Article |
Language: | zho |
Published: |
Editorial Department of Journal on Communications
2021-08-01
|
Series: | Tongxin xuebao |
Subjects: | |
Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021128/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Effects and optimization of pilot sequence length on rate in multiuser massive MIMO FDD system
by: Yi WANG, et al.
Published: (2018-07-01) -
Intelligent CSI feedback method for fast time-varying FDD massive MIMO system
by: Yong LIAO, et al.
Published: (2021-07-01) -
Research on CSI feedback and precoding in FDD cell-free massive MIMO systems
by: ZHANG Dekun, et al.
Published: (2024-12-01) -
Research on CSI feedback of RIS-assisted massive MIMO system based on manifold learning
by: QIAN Mujun, et al.
Published: (2024-12-01) -
Research and evaluation of sparse array for massive MIMO
by: Mengting LOU, et al.
Published: (2021-09-01)