2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 2018
DOI: 10.1109/spawc.2018.8445972
|View full text |Cite
|
Sign up to set email alerts
|

Bayesian Learning Based Millimeter-Wave Sparse Channel Estimation with Hybrid Antenna Array

Abstract: We consider the problem of millimeter-wave (mmWave) channel estimation with a hybrid digital-analog twostage beamforming structure. A radio frequency (RF) chain excites a dedicated set of antenna subarrays. To compensate for the severe path loss, known training signals are beamformed and swept to scan the angular space. Since the mmWave channels typically exhibit sparsity, the channel response can usually be expressed as a linear combination of a small number of scattering clusters. Thereby the number of angle… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2019
2019
2022
2022

Publication Types

Select...
2
1

Relationship

1
2

Authors

Journals

citations
Cited by 3 publications
references
References 15 publications
0
0
0
Order By: Relevance