Active Inference for Sum Rate Maximization in UAV-Assisted Cognitive NOMA Networks

F Obite, A Krayani, AS Alam, L Marcenaro… - arXiv preprint arXiv …, 2023 - arxiv.org
Given the surge in wireless data traffic driven by the emerging Internet of Things (IoT),
unmanned aerial vehicles (UAVs), cognitive radio (CR), and non-orthogonal multiple access …

[Retracted] Dynamic Data‐Driven Modelling of Water Allocation for the Internet of Things

Z Du, Z Dong - Wireless Communications and Mobile …, 2022 - Wiley Online Library
The allocation of water resources is an important aspect of maintaining public security, but
there are still many problems in water resources management. The application of IoT …

Proactive Network Fault Management for Reliable Subscribed Network Slicing in Software‐Defined Mobile Data IoT Services

S Math, P Tam, S Kim - Scientific Programming, 2022 - Wiley Online Library
Proactive network solutions (PNS) become the precise management and orchestration
(MANO) in the applied artificial intelligence (AI) era. The PNS proposed to invent future …

DDPG with Transfer Learning and Meta Learning Framework for Resource Allocation in Underlay Cognitive Radio Network

N Mishra, S Srivastava, SN Sharan - Wireless Personal Communications, 2023 - Springer
Cognitive Radio (CR) is an intelligent device equipped with a Cognitive Engine (CE)
capable of making decisions and finding the best policy for a dynamic network. Superior …

Hybrid Multiple Access Resource Allocation based on Multi-agent Deep Transfer Reinforcement Learning

Y Zhang, X Wang, D Li, Y Xu - 2022 IEEE 95th Vehicular …, 2022 - ieeexplore.ieee.org
In order to reduce the consumption cost for successive interference cancellation in non-
orthogonal multiple access (NOMA), we propose a resource allocation scheme that involves …

Resource allocation in multi-user cellular networks: A transformer-based deep reinforcement learning approach

Z Di, Z Zhong, Q Pengfei, Q Hao… - China Communications, 2024 - ieeexplore.ieee.org
To meet the communication services with diverse requirements, dynamic resource allocation
has shown increasing importance. In this paper, we consider the multi-slot and multi-user …

Reinforcement learning empowered unmanned aerial vehicle assisted internet of things networks

SK Mahmud - 2023 - qmro.qmul.ac.uk
This thesis aims towards performance enhancement for unmanned aerial vehicles (UAVs)
assisted internet of things network (IoT). In this realm, novel reinforcement learning (RL) …

Optimal Energy Efficiency Used DDPG in IRS-NOMA Wireless Communications

Q Liu, J Wu, L Hu, S Bi, W Ji, R Yang - Symmetry, 2022 - mdpi.com
Combining Intelligent Reflecting Surface (IRS) with Non-Orthogonal Multiple Access
(NOMA) technology is a viable option for increasing communication performance. Firstly, a …

Energy‐Efficient Resource Allocation for NOMA‐Enabled Internet of Vehicles

X Chen, Z Ma, T Ma, X Liu… - … and Mobile Computing, 2021 - Wiley Online Library
With the rapid development of Internet of vehicles (IoV) technology, the distribution of
vehicles on the highway becomes more dense and the highly reliable communication …

Underlay Cognitive Radio Resource Management with Hybrid Meta-Loss Learning

N Mishra, S Srivastava, SN Sharan - Iranian Journal of Science and …, 2024 - Springer
Cognitive Radio (CR) is an adaptable communication device driven by a Cognitive Engine
(CE). A suitable machine-learning strategy can increase the learning potential of CE. This …