Dictionary learning-based sparse channel representation and estimation for FDD massive MIMO systems

Y Ding, BD Rao - IEEE Transactions on Wireless …, 2018 - ieeexplore.ieee.org
This paper addresses the problem of uplink (UL) and downlink (DL) channel estimation in
frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems …
被引用次数：149 相关文章

[引用][C] Dictionary Learning-Based Sparse Channel Representation and Estimation for FDD Massive MIMO Systems

Y Ding, BD Rao - IEEE Transactions on Wireless Communications, 2018 - cir.nii.ac.jp
Dictionary Learning-Based Sparse Channel Representation and Estimation for FDD Massive
MIMO Systems | CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ …

Dictionary Learning-Based Sparse Channel Representation and Estimation for FDD Massive MIMO Systems

Y Ding, BD Rao - IEEE Transactions on Wireless Communications, 2018 - dl.acm.org
This paper addresses the problem of uplink (UL) and downlink (DL) channel estimation in
frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems …
[PDF] ieee.org

[PDF][PDF] Dictionary Learning Based Sparse Channel Representation and Estimation for FDD Massive MIMO Systems

Y Ding, BD Rao - ieeexplore.ieee.org
This paper addresses the problem of uplink and downlink channel estimation in FDD
Massive MIMO systems. By utilizing sparse recovery and compressive sensing algorithms …

Dictionary Learning Based Sparse Channel Representation and Estimation for FDD Massive MIMO Systems

Y Ding, BD Rao - arXiv e-prints, 2016 - ui.adsabs.harvard.edu
This paper addresses the problem of uplink and downlink channel estimation in FDD
Massive MIMO systems. By utilizing sparse recovery and compressive sensing algorithms …

Dictionary Learning Based Sparse Channel Representation and Estimation for FDD Massive MIMO Systems

Y Ding, BD Rao - arXiv preprint arXiv:1612.06553, 2016 - arxiv.org
This paper addresses the problem of uplink and downlink channel estimation in FDD
Massive MIMO systems. By utilizing sparse recovery and compressive sensing algorithms …