Towards real-time, machine learning enhanced signal detection in 5G-NR
S Brennsteiner - 2023 - era.ed.ac.uk
Mobile communication technology is essential in our connected society. In 2022, the
deployment of the 5th Generation New Radio (5G-NR) standard is well on its way in many …
deployment of the 5th Generation New Radio (5G-NR) standard is well on its way in many …
Regularized Neural Detection for One-Bit Massive MIMO Communication Systems
A Sant, BD Rao - arXiv preprint arXiv:2305.15543, 2023 - arxiv.org
Detection for one-bit massive MIMO systems presents several challenges especially for
higher order constellations. Recent advances in both model-based analysis and deep …
higher order constellations. Recent advances in both model-based analysis and deep …
An efficient ADMM-aided deep learning-based signal detector for uplink massive MIMO
H Huang, JM Cioffi, SA Hashemi - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
This paper provides an efficient Alternating Direction Method of Multipliers (ADMM)-aided
deep neural network (DNN) framework for signal detection based on uplink Massive Multiple …
deep neural network (DNN) framework for signal detection based on uplink Massive Multiple …
Deep learning for massive MIMO uplink detectors
MA Albreem, AH Alhabbash… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Detection techniques for massive multiple-input multiple-output (MIMO) have gained a lot of
attention in both academia and industry. Detection techniques have a significant impact on …
attention in both academia and industry. Detection techniques have a significant impact on …
LAMANet: A real-time, machine learning-enhanced approximate message passing detector for massive MIMO
S Brennsteiner, T Arslan, JS Thompson… - … Transactions on Very …, 2022 - ieeexplore.ieee.org
Model-driven machine learning for signal detection in the physical layer of mobile
communication systems combines well-known detector structures with learned parameters …
communication systems combines well-known detector structures with learned parameters …
Adaptive neural signal detection for massive MIMO
Traditional symbol detection algorithms either perform poorly or are impractical to implement
for Massive Multiple-Input Multiple-Output (MIMO) systems. Recently, several learning …
for Massive Multiple-Input Multiple-Output (MIMO) systems. Recently, several learning …
Regularized Neural Detection for Millimeter Wave Massive Mimo Communication Systems with One-Bit Adcs
Multi-user massive MIMO signal detection from one-bit received measurements strongly
depends on the wireless channel. To this end, majority of the model and learning-based …
depends on the wireless channel. To this end, majority of the model and learning-based …
Leveraging deep neural networks for massive MIMO data detection
Massive multiple-input multiple-output (MIMO) is a key technology for emerging next-
generation wireless systems. Utilizing large antenna arrays at base-stations, massive MIMO …
generation wireless systems. Utilizing large antenna arrays at base-stations, massive MIMO …
Enhanced deep learning for massive MIMO detection using approximate matrix inversion
AJ Almasadeh, KA Alnajjar… - 2022 5th International …, 2022 - ieeexplore.ieee.org
Massive multiple-input multiple-output (MIMO) is a crucial technology in fifth-generation (5G)
and beyond 5G (B5G). However, the huge number of antennas used in massive MIMO …
and beyond 5G (B5G). However, the huge number of antennas used in massive MIMO …
A data-driven deep learning network for massive MIMO detection with high-order QAM
Y Yu, J Ying, P Wang, L Guo - Journal of Communications and …, 2023 - ieeexplore.ieee.org
Massive multiple-input multiple-output (MIMO) can provide higher spectral efficiency and
energy efficiency compared to conventional MIMO systems. Unfortunately, as the numbers of …
energy efficiency compared to conventional MIMO systems. Unfortunately, as the numbers of …