Measurement-Based Prediction of mmWave Channel Parameters Using Deep Learning and Point Cloud
Millimeter-wave (MmWave) channel characteristics are quite different from sub-6 GHz frequency bands. The major differences include higher path loss and sparser multipath components (MPCs), resulting in more significant time-varying characteristics in mmWave channels. It is difficult to characterize...
Saved in:
Main Authors: | Hang Mi, Bo Ai, Ruisi He, Anuraag Bodi, Raied Caromi, Jian Wang, Jelena Senic, Camillo Gentile, Yang Miao |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Open Journal of Vehicular Technology |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10620622/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Low pilot overhead parametric channel estimation scheme for RIS-assisted mmWave MIMO systems
by: LI Shuangzhi, et al.
Published: (2024-09-01) -
Low-complexity massive MIMO channel estimation for mmWave systems via matrix completion
by: Jiafeng QIU
Published: (2020-04-01) -
Orthogonal beam codebook based hybrid precoding algorithm for mmWave MIMO system
by: Weiting ZHAO, et al.
Published: (2017-07-01) -
Low complexity hybrid precoding method in mmWave massive MIMO system
by: Jianwei XIANG, et al.
Published: (2016-09-01) -
Adaptive gradient algorithm for hybrid precoding in mmWave MIMO system
by: Yu ZHANG, et al.
Published: (2021-10-01)