Application of reinforcement learning and deep learning in multiple-input and multiple-output (MIMO) systems

M Naeem, G De Pietro, A Coronato - Sensors, 2021 - mdpi.com
The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …

BDMA for millimeter-wave/terahertz massive MIMO transmission with per-beam synchronization

L You, X Gao, GY Li, XG Xia… - IEEE Journal on Selected …, 2017 - ieeexplore.ieee.org
We propose beam division multiple access (BDMA) with per-beam synchronization (PBS) in
time and frequency for wideband massive multiple-input multiple-output (MIMO) …

Channel acquisition for massive MIMO-OFDM with adjustable phase shift pilots

L You, X Gao, AL Swindlehurst… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
We propose adjustable phase shift pilots (APSPs) for channel acquisition in wideband
massive multiple-input multiple-output (MIMO) systems employing orthogonal frequency …

Massive MIMO wireless networks: An overview

N Hassan, X Fernando - Electronics, 2017 - mdpi.com
Massive multiple-input-multiple-output (MIMO) systems use few hundred antennas to
simultaneously serve large number of wireless broadband terminals. It has been …

Sum-rate and power scaling of massive MIMO systems with channel aging

C Kong, C Zhong… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
This paper investigates the achievable sum-rate of massive multiple-input multiple-output
(MIMO) systems in the presence of channel aging. For the uplink, by assuming that the base …

Intelligent wireless communications enabled by cognitive radio and machine learning

X Zhou, M Sun, GY Li, BHF Juang - China Communications, 2018 - ieeexplore.ieee.org
The ability to intelligently utilize resources to meet the need of growing diversity in services
and user behavior marks the future of wireless communication systems. Intelligent wireless …

Cooperative power-domain NOMA systems: an overview

M Ghous, AK Hassan, ZH Abbas, G Abbas, A Hussien… - Sensors, 2022 - mdpi.com
Interference has been a key roadblock against the effectively deployment of applications for
end-users in wireless networks including fifth-generation (5G) and beyond fifth-generation …

Lightweight convolutional neural networks for CSI feedback in massive MIMO

Z Cao, WT Shih, J Guo, CK Wen… - IEEE Communications …, 2021 - ieeexplore.ieee.org
In frequency division duplex mode of massive multiple-input multiple-output systems, the
downlink channel state information (CSI) must be sent to the base station (BS) through a …

Deep reinforcement learning paradigm for performance optimization of channel observation–based MAC protocols in dense WLANs

R Ali, N Shahin, YB Zikria, BS Kim, SW Kim - IEEE Access, 2018 - ieeexplore.ieee.org
The potential applications of deep learning to the media access control (MAC) layer of
wireless local area networks (WLANs) have already been progressively acknowledged due …

Pilot power allocation through user grouping in multi-cell massive MIMO systems

P Liu, S Jin, T Jiang, Q Zhang… - Ieee transactions on …, 2016 - ieeexplore.ieee.org
In this paper, we propose a relative channel estimation error (RCEE) metric, and derive
closed-form expressions for its expectation Exprcee and the achievable uplink rate holding …