Slice admission control in 5G cloud radio access network using deep reinforcement learning: A survey

M Khani, S Jamali, MK Sohrabi… - International Journal …, 2024 - Wiley Online Library
The emergence of 5G networks has increased the demand for network resources, making
efficient resource management crucial. Slice admission control (SAC) is a process that …

Explanation-Guided Deep Reinforcement Learning for Trustworthy 6G RAN Slicing

F Rezazadeh, H Chergui… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
The complexity of emerging sixth-generation (6G) wireless networks has sparked an
upsurge in adopting artificial intelligence (AI) to underpin the challenges in network …

A supervised active learning method for identifying critical nodes in IoT networks

B Ojaghi, MM Dehshibi, A Antonopoulos - The Journal of Supercomputing, 2024 - Springer
The energy efficiency of wireless sensor networks (WSNs) as a key feature of the Internet of
Things (IoT) and fifth-generation (5G) mobile networks is determined by several key …

Graphical modelling and optimization of ran function split deployed through uavs

G Mountaser, E Pardo, T Mahmoodi - Computer Networks, 2022 - Elsevier
In this paper, we demonstrate the potentials of deploying radio access network function split
architecture through aerial network and present a graph-based model to analyse and …

Towards quantum-enabled 6G slicing

F Rezazadeh, S Kahvazadeh… - arXiv preprint arXiv …, 2022 - arxiv.org
The quantum machine learning (QML) paradigms and their synergies with network slicing
can be envisioned to be a disruptive technology on the cusp of entering to era of sixth …