Intelligent resource management using multiagent double deep Q-networks to guarantee strict reliability and low latency in IoT network

A Salh, R Ngah, GA Hussain, L Audah… - IEEE Open Journal …, 2022 - ieeexplore.ieee.org
With the rapid adoption of the Internet of Things, it is necessary to go beyond fifth-generation
applications and apply stringent high reliability and low latency requirements, closely related …

Meta Federated Reinforcement Learning for Distributed Resource Allocation

Z Ji, Z Qin, X Tao - IEEE Transactions on Wireless …, 2023 - ieeexplore.ieee.org
In cellular networks, resource allocation is usually performed in a centralized way, which
brings huge computation complexity to the base station (BS) and high transmission …

Energy Efficient QoS Aware Machine Learning Model for Scheduling Users in NOMA Heterogeneous Networks

ML Moses, T Perarasi, MR Raja… - … and Robotics (STCR), 2022 - ieeexplore.ieee.org
The massive growth in mobile devices and machine type communication devices which
demands higher performance leads to higher data traffic and spectrum scarcity problem …

Deep Reinforcement Learning for Uplink Multi-Carrier Non-Orthogonal Multiple Access Resource Allocation Using Buffer State Information

EM Bansbach, Y Kiyak… - European Wireless 2022; …, 2022 - ieeexplore.ieee.org
For orthogonal multiple access (OMA) systems, the number of served user equipments
(UEs) is limited to the number of available orthogonal resources. On the other hand, non …

Hybrid cascaded attention-guided refinement network-based optimal power allocation in MIMO-NOMA system

A Kumar - International Conference on Mathematical and …, 2023 - spiedigitallibrary.org
The multiple input multiple output (MIMO) plays an integral role in improving the energy
efficiency for enhancing the QoS of all users. For the 5G wireless communication (WC) …