A review of deep learning in 5G research: Channel coding, massive MIMO, multiple access, resource allocation, and network security

A Ly, YD Yao - IEEE Open Journal of the Communications …, 2021 - ieeexplore.ieee.org
The current development of 5G technology is flourishing with widespread deployment
across the world at a rapid pace. However, there is still a demand concerning 5G research …

Deep learning based physical layer security for terrestrial communications in 5G and beyond networks: A survey

H Sharma, N Kumar - Physical Communication, 2023 - Elsevier
The key principle of physical layer security (PLS) is to permit the secure transmission of
confidential data using efficient signal-processing techniques. Also, deep learning (DL) has …

Deep learning based radio resource management in NOMA networks: User association, subchannel and power allocation

H Zhang, H Zhang, K Long… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
With the rapid development of future wireless communication, the combination of NOMA
technology and millimeter-wave (mmWave) technology has become a research hotspot. The …

[HTML][HTML] Modeling of NOMA-MIMO-Based Power Domain for 5G Network under Selective Rayleigh Fading Channels

M Hassan, M Singh, K Hamid, R Saeed, M Abdelhaq… - Energies, 2022 - mdpi.com
The integration of multiple-input multiple-output (MIMO) and non-orthogonal multiple access
(NOMA) technologies is a hybrid technology that overcomes a myriad of problems in the 5G …

Deep learning-based joint NOMA signal detection and power allocation in cognitive radio networks

A Kumar, K Kumar - IEEE Transactions on Cognitive …, 2022 - ieeexplore.ieee.org
Presently, Non-Orthogonal Multiple Access (NOMA) frequently uses Successive Interference
Cancellation (SIC) with channel estimation to detect the receivers' signal successfully …

Signal processing and learning for next generation multiple access in 6G

W Chen, Y Liu, H Jafarkhani, YC Eldar, P Zhu… - arXiv preprint arXiv …, 2023 - arxiv.org
Wireless communication systems to date primarily rely on the orthogonality of resources to
facilitate the design and implementation, from user access to data transmission. Emerging …

[HTML][HTML] Power allocation and user grouping for NOMA downlink systems

J Li, T Gao, B He, W Zheng, F Lin - Applied Sciences, 2023 - mdpi.com
Non-orthogonal multiple access (NOMA) technology allows multiple users to use the same
time-frequency resource to send signals, which can improve spectral efficiency and …

[HTML][HTML] Deep neural network (DNN) for efficient user clustering and power allocation in downlink non-orthogonal multiple access (NOMA) 5G networks

SP Kumaresan, CK Tan, YH Ng - Symmetry, 2021 - mdpi.com
Non-orthogonal multiple access (NOMA) emerges as a promising candidate for 5G, which
radically alters the way users share the spectrum. In the NOMA system, user clustering (UC) …

Uplink NOMA signal transmission with convolutional neural networks approach

LIN Chuan, C Qing, LI Xianxu - Journal of Systems Engineering …, 2020 - ieeexplore.ieee.org
Non-orthogonal multiple access (NOMA), featuring high spectrum efficiency, massive
connectivity and low latency, holds immense potential to be a novel multi-access technique …

Energy-efficient power allocation in downlink multi-cell multi-carrier NOMA: Special deep neural network framework

ABM Adam, Z Wang, X Wan, Y Xu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Energy-efficient resource allocation for multi-cell multi-carrier non-orthogonal multiple
access (MCMC-NOMA) is a challenging task due to the interference and other related …