Machine Learning Based Critical Resource Allocation in Mixed-Traffic Cellular Networks

M Nomeir - 2021 - fount.aucegypt.edu
… They also state that the requirements can be met if the 5G numerology with 2 symbols/
slot with 15 KHz spacing. In [36], the GF procedure is discussed in detail along with its …

Transfer learning promotes 6G wireless communications: Recent advances and future challenges

M Wang, Y Lin, Q Tian, G Si - IEEE Transactions on Reliability, 2021 - ieeexplore.ieee.org
… between the learning agent and the underlying environment, and the learning agent uses
future … In order to create autonomous wireless systems, we need to mix different software …

Resource management in wireless networks

M Raftopoulou - 2024 - research.tudelft.nl
… characterise agents by their importance in the learning pro… of the packet schedulers and
the numerology on the QoS (i) … and (ii) a non-sliced scenario with mixed LC/TO traffic. We then …

Deep Reinforcement Learning for Scalable Dynamic Bandwidth Allocation in RAN Slicing with Highly Mobile Users

S Choi, S Choi, G Lee, SG Yoon… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
… maximization problem formulated by mixed-integer nonlinear … : i) How to prevent the agent
from learning a selfish policy that … and users on numerology 1. That is, the bandwidth and time …

Programmable and customized intelligence for traffic steering in 5G networks using open RAN architectures

A Lacava, M Polese, R Sivaraj… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
agent to learn an accurate representation of the system. Then, when it comes to closedloop
control through Deep Reinforcement Learning (… of learning a table of Q-values, we learn the …

Radio Access Network Slicing and Virtualization for 5G Vertical Industries

L Zhang, A Farhang, G Feng, O Onireti - Wiley Online Library
… While beginners can learn about the novel techniques to … mixed numerology, and Part II is
focused on layers higher than PHY. … Then a multi-agent reinforcement learning based smart …

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
… the SCS numerologyagent can be misleading when the information and reward are not
accurate [27]. To accurately judge an agent’s selected action, we adopt an intermittent learning

MUESLI: Multi-objective radio resource slice management via reinforcement learning

A Kattepur, S David, S Mohalik - 2022 IEEE 8th International …, 2022 - ieeexplore.ieee.org
… The principle is that timefrequency resources with the same numerology are grouped together
… puts the traffic mix and the intent requirements to be met by the slices. Table II provides an …

On enabling 5G dynamic TDD by leveraging deep reinforcement learning and O-RAN

K Boutiba, M Bagaa, A Ksentini - NOMS 2023-2023 IEEE/IFIP …, 2023 - ieeexplore.ieee.org
… We define the DRP design by: State: The DRP agent considers … The base station uses
numerology 1 and a TDD period of 5ms. … The Mixed slot is required between UL and DL slots to …

AI-enabled energy-aware carrier aggregation in 5G new radio with dual connectivity

F Khoramnejad, R Joda, AB Sediq, G Boudreau… - IEEE …, 2023 - ieeexplore.ieee.org
… We first model it as a multi-agent reinforcement learning (RL) system with compound action
… as a mixed-integer optimization problem. The transformation and variable substitution have …