A survey of machine learning techniques applied to self-organizing cellular networks

PV Klaine, MA Imran, O Onireti… - … Surveys & Tutorials, 2017 - ieeexplore.ieee.org
In this paper, a survey of the literature of the past 15 years involving machine learning (ML)
algorithms applied to self-organizing cellular networks is performed. In order for future …

Towards artificial intelligence enabled 6G: State of the art, challenges, and opportunities

S Zhang, D Zhu - Computer Networks, 2020 - Elsevier
Abstract 6G is expected to support the unprecedented Internet of everything scenarios with
extremely diverse and challenging requirements. To fulfill such diverse requirements …

[HTML][HTML] Intent-based networks for 6G: Insights and challenges

Y Wei, M Peng, Y Liu - Digital Communications and Networks, 2020 - Elsevier
Abstract Intent-Based Networks (IBNs), which are originally proposed to introduce Artificial
Intelligence (AI) into the sixth-generation (6G) wireless networks, can effectively solve the …

Comprehensive survey on self-organizing cellular network approaches applied to 5G networks

H Fourati, R Maaloul, L Chaari, M Jmaiel - Computer Networks, 2021 - Elsevier
Abstract Self-Organizing Network (SON) stands for a key concept characterizing the
behavior of the future mobile networks. The evolution of telecom infrastructures towards 5G …

A survey of online data-driven proactive 5G network optimisation using machine learning

B Ma, W Guo, J Zhang - IEEE access, 2020 - ieeexplore.ieee.org
In the fifth-generation (5G) mobile networks, proactive network optimisation plays an
important role in meeting the exponential traffic growth, more stringent service requirements …

Reinforcement learning-based downlink interference control for ultra-dense small cells

L **ao, H Zhang, Y **ao, X Wan, S Liu… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
The dense deployment of small cells in 5G cellular networks raises the issue of controlling
downlink inter-cell interference under time-varying channel states. In this paper, we propose …

A review of machine learning techniques for enhanced energy efficient 5G and 6G communications

TP Fowdur, B Doorgakant - Engineering Applications of Artificial …, 2023 - Elsevier
Cellular technologies have evolved continuously from the 1st to the 5th generation (5G) to
meet the exponentially growing needs of bandwidth, throughput and latency. However, the …

Data-driven resource management for ultra-dense small cells: An affinity propagation clustering approach

LC Wang, SH Cheng - IEEE Transactions on Network Science …, 2018 - ieeexplore.ieee.org
Deploying dense small cells is the key to providing high capacity, but raise the serious issue
of energy consumption and inter-cell interference. To understand the behaviors of ultra …

Reinforcement learning-based interference control for ultra-dense small cells

H Zhang, M Min, L **ao, S Liu… - 2018 IEEE Global …, 2018 - ieeexplore.ieee.org
The densification deployment of small cells emerging into 5G cellular networks can achieve
high capacity, but is faced with the challenge of how to manage energy consumption and …

Self-organizing cellular network approaches applied to 5G networks

H Fourati, R Maaloul, L Chaari - 2019 Global Information …, 2019 - ieeexplore.ieee.org
SON is an interesting topic in today's cellular networks. Indeed, heterogeneous networks,
ultra-dense deployments and diverse Radio Access Technologies in the same operating …