FDD massive MIMO via UL/DL channel covariance extrapolation and active channel sparsification

MB Khalilsarai, S Haghighatshoar… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
We propose a novel method for massive multiple-input multiple-output (massive MIMO) in
frequency division duplexing (FDD) systems. Due to the large frequency separation between …

Compressed sensing-aided downlink channel training for FDD massive MIMO systems

Y Han, J Lee, DJ Love - IEEE Transactions on Communications, 2017 - ieeexplore.ieee.org
There is much discussion in industry and academia about possible technical solutions to
address the growth in demand for wireless broadband. Massive multiple-input multiple …

Deep learning and compressive sensing-based CSI feedback in FDD massive MIMO systems

P Liang, J Fan, W Shen, Z Qin… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
To fully utilize multiplexing and array gains of massive multiple-input multiple-output (MIMO),
the downlink channel state information (CSI) must be acquired at the base station (BS). In …

Efficient compressive sensing based sparse channel estimation for 5G massive MIMO systems

I Khan, D Singh - AEU-International Journal of Electronics and …, 2018 - Elsevier
Massive MIMO (multiple-input-multiple-output) is one of the key technologies of 5G mobile
cellular networks, which can form a huge antenna array by providing a large number of …

Exploiting burst-sparsity in massive MIMO with partial channel support information

A Liu, VKN Lau, W Dai - IEEE Transactions on Wireless …, 2016 - ieeexplore.ieee.org
How to obtain accurate channel state information at the base station (CSIT) is a key
implementation challenge behind frequency-division duplex massive MIMO systems …

Structured compressive sensing based superimposed pilot design in downlink large‐scale MIMO systems

Z Gao, L Dai, Z Wang - Electronics Letters, 2014 - Wiley Online Library
Large‐scale multiple‐input multiple‐output (MIMO) with high spectrum and energy efficiency
is a very promising key technology for future 5G wireless communications. For large‐scale …

Beam squint and channel estimation for wideband mmWave massive MIMO-OFDM systems

B Wang, M Jian, F Gao, GY Li… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
With the increasing scale of antenna arrays in wideband millimeter-wave (mmWave)
communications, the physical propagation delays of electromagnetic waves traveling across …

Data-driven deep learning to design pilot and channel estimator for massive MIMO

X Ma, Z Gao - IEEE Transactions on Vehicular Technology, 2020 - ieeexplore.ieee.org
In this paper, we propose a data-driven deep learning (DL) approach to jointly design the
pilot signals and channel estimator for wideband massive multiple-input multiple-output …

An overview of low-rank channel estimation for massive MIMO systems

H Xie, F Gao, S Jin - IEEE Access, 2016 - ieeexplore.ieee.org
Massive multiple-input multiple-output is a promising physical layer technology for 5G
wireless communications due to its capability of high spectrum and energy efficiency, high …

Sparse channel estimation via hierarchical hybrid message passing for massive MIMO-OFDM systems

X Liu, W Wang, X Song, X Gao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this paper, we investigate a sparse channel estimation problem for broadband massive
multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) …