Integrated sensing and communications with joint beam-squint and beam-split for mmWave/THz massive MIMO

F Gao, L Xu, S Ma - IEEE Transactions on Communications, 2023 - ieeexplore.ieee.org
Integrated sensing and communications (ISAC) has attracted tremendous attention for the
future 6G wireless communications systems. To improve the transmission rates and sensing …

Deep learning for super-resolution channel estimation and DOA estimation based massive MIMO system

H Huang, J Yang, H Huang, Y Song… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
The recent concept of massive multiple-input multiple-output (MIMO) can significantly
improve the capacity of the communication network, and it has been regarded as a …

Deep Learning-Aided Delay-Tolerant Zero-Forcing Precoding in Cell-Free Massive MIMO

W Jiang, HD Schotten - 2022 IEEE 96th Vehicular Technology …, 2022 - ieeexplore.ieee.org
In the context of cell-free massive multi-input multi-output (CFmMIMO), zero-forcing
precoding (ZFP) is superior in terms of spectral efficiency. However, it suffers from channel …

Energy-efficient multi-antenna hybrid block diagonalization precoding and combining for mmWave massive multi-user MIMO systems

Y Zhang, Y Lian, Y Liu, Q Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-
MIMO) can significantly improve the throughput and spectral efficiency by equipping multi …

Machine learning inspired energy-efficient hybrid precoding for mmWave massive MIMO systems

X Gao, L Dai, Y Sun, S Han… - 2017 IEEE International …, 2017 - ieeexplore.ieee.org
Hybrid precoding is a promising technique for mmWave massive MIMO systems, as it can
considerably reduce the number of required radio-frequency (RF) chains without obvious …

Modeling, analysis, and optimization of grant-free NOMA in massive MTC via stochastic geometry

J Liu, G Wu, X Zhang, S Fang… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
In the massive machine-type communications (mMTCs) scenario for Internet-of-Things (IoTs)
applications, though a large number of devices are registered to an access point (AP), very …

Neural-network optimized 1-bit precoding for massive MU-MIMO

A Balatsoukas-Stimming, O Castañeda… - 2019 IEEE 20th …, 2019 - ieeexplore.ieee.org
Base station (BS) architectures for massive multiuser (MU) multiple-input multiple-output
(MIMO) wireless systems are equipped with hundreds of antennas to serve tens of users on …

Robust symbol-level precoding via autoencoder-based deep learning

F Sohrabi, HV Cheng, W Yu - ICASSP 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
This paper proposes an autoencoder-based symbol-level precoding (SLP) scheme for a
massive multiple-input multiple-output (MIMO) system operating in a limited-scattering …

Over-sampling codebook-based hybrid minimum sum-mean-square-error precoding for millimeter-wave 3D-MIMO

J Mao, Z Gao, Y Wu, MS Alouini - IEEE Wireless …, 2018 - ieeexplore.ieee.org
Hybrid precoding design is challenging for millimeter-wave massive MIMO. Most prior hybrid
precoding schemes are designed to maximize the sum spectral efficiency, while seldom …

Hybrid precoding design for two-way relay-assisted terahertz massive MIMO systems

T Mir, M Waqas, U Mir, SM Hussain, AM Elbir… - IEEE Access, 2020 - ieeexplore.ieee.org
Hybrid precoding has emerged as a promising technique to reduce the hardware cost and
complexity in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) …