Grant-Free NOMA: A Low-Complexity Power Control through User Clustering

A Celik - Sensors, 2023 - mdpi.com
Non-orthogonal multiple access (NOMA) has emerged as a promising solution to support
multiple devices on the same network resources, improving spectral efficiency and enabling …

Safeguarding Next Generation Multiple Access Using Physical Layer Security Techniques: A Tutorial

L Lv, D Xu, RQ Hu, Y Ye, L Yang, X Lei, X Wang… - arXiv preprint arXiv …, 2024 - arxiv.org
Driven by the ever-increasing requirements of ultra-high spectral efficiency, ultra-low
latency, and massive connectivity, the forefront of wireless research calls for the design of …

AI/ML-aided capacity maximization strategies for URLLC in 5G/6G wireless systems: A survey

RB Shaik, P Nagaradjane, I Ioannou, V Sittakul… - Computer Networks, 2024 - Elsevier
Ultra-reliable low-latency communication (URLLC) refers to cellular applications in fifth and
sixth-generation (5G/6G) networks with specific latency, reliability, and availability demands …

[HTML][HTML] Advancing 6G IoT networks: Willow Catkin packet transmission scheduling with AI and Bayesian game-theoretic approach-based resource allocation.

AMA Ibrahim, Z Chen, HA Eljailany, G Yu, AA Ipaye… - Internet of Things, 2024 - Elsevier
The rapid expansion of mobile broadband networks and the proliferation of Internet of
Things (IoT) applications have substantially increased data transmission and processing …

Optimization of Energy Efficiency for Uplink mURLLC Over Multiple Cells Using Cooperative Multi-Agent Reinforcement Learning

Q Song, FC Zheng, J Luo - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Multi-agent reinforcement learning (RL) has recently been adopted to solve massive ultra-
reliable and low-latency communications (mURLLC) energy efficiency (EE) optimization …

Reinforcement Learning for QoE-Oriented Flexible Bandwidth Allocation in Satellite Communication Networks

TM Kebedew, VN Ha, E Lagunas… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
Optimizing the use of satellite bandwidth to achieve maximum return in a system where user
demands are constantly changing, and application-specific Quality-of-Experience (QoE) …

A Hybrid Optimization and Deep RL Approach for Resource Allocation in Semi-GF NOMA Networks

DD Tran, VN Ha, S Chatzinotas… - 2023 IEEE 34th Annual …, 2023 - ieeexplore.ieee.org
Semi-grant-free non-orthogonal multiple access (semi-GF NOMA) has emerged as a
promising technology for the fifth-generation new radio (5G-NR) networks supporting the …

Subcarrier power control for URLLC communication system via multi-agent deep reinforcement learning in IoT network

H Wang, X Li, F Luo, J Li… - International Journal of …, 2024 - inderscienceonline.com
Designing an intelligent resource allocation scheme to achieve the performance
requirements of internet of things (IoT) devices for the future ultra-reliable low-latency …

Q-Learning-Augmented Grant-Free NOMA for URLLC

I Oueslati, O Habachi, JP Cances, V Meghdadi… - International Symposium …, 2023 - Springer
Abstract Grant-Free (GF) Non-Orthogonal Multiple Access (GF-NOMA) has emerged as a
promising technology for 5G networks requiring Ultra-Reliable Low Latency …

Q-Learning-Augmented Grant-Free NOMA for URLLC

V Meghdadi, E Sabir - LNCS 14757 Ubiquitous Networking - Springer
Grant-Free (GF) Non-Orthogonal Multiple Access (GFNOMA) has emerged as a promising
technology for 5G networks requiring Ultra-Reliable Low Latency Communications …