Deep reinforcement learning for resource allocation in 5G communications

ML Tham, A Iqbal, YC Chang - 2019 Asia-Pacific Signal and …, 2019 - ieeexplore.ieee.org
The rapid growth of data traffic has pushed the mobile telecommunication industry towards
the adoption of fifth generation (5G) communications. Cloud radio access network (CRAN) …

Resource allocation for joint energy and spectral efficiency in cloud radio access network based on deep reinforcement learning

A Iqbal, ML Tham, YC Chang - Transactions on Emerging …, 2022 - Wiley Online Library
The rapid increase of user data traffic demand has promoted the telecommunication sector
toward adopting a new generation, that is, fifth‐generation (5G). Cloud radio access network …

Deep reinforcement learning based dynamic resource allocation in cloud radio access networks

RT Rodoshi, T Kim, W Choi - 2020 International Conference on …, 2020 - ieeexplore.ieee.org
Cloud radio access network (C-RAN) is a promising architecture to fulfill the ever-increasing
resource demand in telecommunication networks. In C-RAN, a base station is decoupled …

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 …

AI-based radio resource allocation in support of the massive heterogeneity of 6G networks

A Alwarafy, A Albaseer, BS Ciftler… - 2021 IEEE 4th 5G …, 2021 - ieeexplore.ieee.org
There is a consensus in industry and academia that 6G wireless networks will incorporate
massive heterogeneous radio access technologies (RATs) in order to cater to the high …

A survey on applications of deep reinforcement learning in resource management for 5G heterogeneous networks

YL Lee, D Qin - 2019 Asia-Pacific Signal and Information …, 2019 - ieeexplore.ieee.org
Heterogeneous networks (HetNets) have been regarded as the key technology for fifth
generation (5G) communications to support the explosive growth of mobile traffics. By …

Learning based e2e energy efficient in joint radio and nfv resource allocation for 5g and beyond networks

N Gholipoor, A Nouruzi, S Salarhosseini… - arXiv preprint arXiv …, 2021 - arxiv.org
In this paper, we propose a joint radio and core resource allocation framework for NFV-
enabled networks. In the proposed system model, the goal is to maximize energy efficiency …

Deep reinforcement learning for edge computing and resource allocation in 5G beyond

Y Dai, D Xu, K Zhang, Y Lu… - 2019 IEEE 19th …, 2019 - ieeexplore.ieee.org
By extending computation capacity to the edge of wireless networks, edge computing has
the potential to enable computation-intensive and delay-sensitive applications in 5G and …

User-Centric Resource Allocation in FD-RAN: A Stepwise Reinforcement Learning Approach

J Chen, J Liu, H Zhou - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
To improve resource utilization flexibility and enhance resource cooperation, a novel fully-
decoupled radio access network (FD-RAN) architecture was conceived, allowing separate …

Double deep Q-network for power allocation in cloud radio access network

A Iqbal, ML Tham, YC Chang - 2020 IEEE 3rd International …, 2020 - ieeexplore.ieee.org
Cloud radio access network (CRAN) facilitates resource allocation (RA) by isolating remote
radio heads (RRHs) from baseband units (BBUs). Traditional RA algorithms save energy by …