ARL-RA: efficient resource allocation in 5G edge networks: a novel intelligent solution using approximate reinforcement learning algorithm

M Khani, S Jamali, MK Sohrabi - Journal of Communication …, 2021 - jce.shahed.ac.ir
The rapid proliferation of fifth-generation (5G) technology has resulted in a wide range of
applications, posing challenges in managing network resources effectively and efficiently …

Reinforcement Learning Based Resource Allocation for Network Slicing in O-RAN

NF Cheng - 2023 - ruor.uottawa.ca
Fifth Generation (5G) introduces technologies that expedite the adoption of mobile networks,
such as densely connected devices, ultra-fast data rate, low latency and more. With those …

Dynamic resource allocation in 5G networks using hybrid RL-CNN model for optimized latency and quality of service

M Karuppiyan, H Subramani… - … in Neural Systems, 2024 - Taylor & Francis
The rapid deployment of 5G networks necessitates innovative solutions for efficient and
dynamic resource allocation. Current strategies, although effective to some extent, lack real …

Intimacy-based resource allocation for network slicing in 5g via deep reinforcement learning

N He, S Yang, F Li, X Chen - IEEE Network, 2021 - ieeexplore.ieee.org
In view of the development of emerging IoT applications driven by artificial intelligence, the
fog radio access network has recently been introduced to fifth generation (5G) wireless …

Resource slicing and customization in RAN with dueling deep Q-network

G Sun, K Xiong, GO Boateng, G Liu, W Jiang - Journal of Network and …, 2020 - Elsevier
The emerging future generation 5G technology is expected to support service-oriented
virtualized networks where different network applications provide unique services. 5G …

Reinforcement learning-based radio access network slicing for a 5G system with support for cellular V2X

HDR Albonda, J Pérez-Romero - … 2019, Poznan, Poland, June 11–12 …, 2019 - Springer
Abstract 5G mobile systems are expected to host a variety of services and applications such
as enhanced mobile broadband (eMBB), massive machine-type communications (mMTC) …

Towards Scalable and Efficient Hierarchical Deep Reinforcement Learning for 5G RAN Slicing

R Huang, M Guo, C Gu, S He, J Chen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As an emerging and promising network paradigm, network slicing creates multiple logical
networks on shared infrastructure to provide services with customized Quality-of-Service …

Energy-efficient deep reinforcement learning assisted resource allocation for 5G-RAN slicing

Y Azimi, S Yousefi, H Kalbkhani… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
One of the pillars of the 5G architecture is network slicing, in which hardware, radio, and
power resources are virtualized as a logical network taking into account the requirements of …

Dynamic Resource Allocation Using a DRL Method in 5G Network

A Kaur, H Sadawarti - International Journal of Intelligent Systems and …, 2023 - ijisae.org
Wireless communication has become increasingly popular in the past two decades. The
purpose of 5G is to provide higher bandwidth, lower latency, greater capacity and enhanced …

Resource allocation in 5G cloud‐RAN using deep reinforcement learning algorithms: A review

M Khani, S Jamali, MK Sohrabi… - Transactions on …, 2024 - Wiley Online Library
This paper reviews recent research on resource allocation in 5G cloud‐based radio access
networks (C‐RAN) using deep reinforcement learning (DRL) algorithms. It explores the …