Deep learning enhanced NOMA system: A survey on future scope and challenges

V Andiappan, V Ponnusamy - Wireless Personal Communications, 2022 - Springer
As a key important approach for next generation communication systems, Non-Orthogonal
Multiple Access (NOMA) has made high attention in the wireless communication. NOMA …

Deep learning-based NOMA system for enhancement of 5G networks: A review

RK Senapati, PJ Tanna - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
The fresh and rising demands for high-reliability and ultrahigh-capacity wireless
communication have led to extensive research into 5G communications. The wide progress …

[HTML][HTML] Deep reinforcement learning-based resource allocation for satellite internet of things with diverse QoS guarantee

S Tang, Z Pan, G Hu, Y Wu, Y Li - Sensors, 2022 - mdpi.com
Large-scale terminals' various QoS requirements are key challenges confronting the
resource allocation of Satellite Internet of Things (S-IoT). This paper presents a deep …

Toward Deep Q-Network-Based Resource Allocation in Industrial Internet of Things

F Liang, W Yu, X Liu, D Griffith… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
With the increasing adoption of Industrial Internet-of-Things (IIoT) devices, infrastructures,
and supporting applications, it is critical to design schemes to effectively allocate resources …

[HTML][HTML] Application of deep learning for quality of service enhancement in internet of things: A review

N Kimbugwe, T Pei, MN Kyebambe - Energies, 2021 - mdpi.com
The role of the Internet of Things (IoT) networks and systems in our daily life cannot be
underestimated. IoT is among the fastest evolving innovative technologies that are digitizing …

Cooperative resource management for cognitive satellite-aerial-terrestrial integrated networks towards IoT

Y Ruan, Y Li, R Zhang, W Cheng, C Liu - IEEE Access, 2020 - ieeexplore.ieee.org
With the ubiquitous deployment of Internet-of-Things (IoT) devices and applications, satellite-
aerial-terrestrial integrated network (SATIN) is regarded as a promising candidate to …

Deep-learning-aided cross-layer resource allocation of OFDMA/NOMA video communication systems

SM Tseng, YF Chen, CS Tsai, WD Tsai - IEEE Access, 2019 - ieeexplore.ieee.org
In previous study, deep learning and autoencoder have been applied for data detection of
NOMA systems, rather than the resource allocation of OFDMA/NOMA systems. In previous …

Revolutionizing future connectivity: A contemporary survey on AI-empowered satellite-based non-terrestrial networks in 6G

S Mahboob, L Liu - IEEE Communications Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Non-Terrestrial Networks (NTN) are expected to be a critical component of 6th Generation
(6G) networks, providing ubiquitous, continuous, and scalable services. Satellites emerge as …

AI based service management for 6G green communications

B Mao, F Tang, K Yuichi, N Kato - arXiv preprint arXiv:2101.01588, 2021 - arxiv.org
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In current 5G and future 6G era, there is no …

Cross-layer resource management for downlink BF-NOMA-OFDMA video transmission systems and supervised/unsupervised learning based approach

SM Tseng, GY Chen, HC Chan - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Ali et al. proposed a physical (PHY) layer resource management for single-carrier N-
antenna beamforming (BF) non-orthogonal multiple access (NOMA) systems. Cross …