Artificial intelligence: A powerful paradigm for scientific research

Y Xu, X Liu, X Cao, C Huang, E Liu, S Qian, X Liu… - The Innovation, 2021 - cell.com
Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well
known from computer science is broadly affecting many aspects of various fields including …

Cellular traffic prediction with machine learning: A survey

W Jiang - Expert Systems with Applications, 2022 - Elsevier
Cellular networks are important for the success of modern communication systems, which
support billions of mobile users and devices. Powered by artificial intelligence techniques …

A tutorial on ultrareliable and low-latency communications in 6G: Integrating domain knowledge into deep learning

C She, C Sun, Z Gu, Y Li, C Yang… - Proceedings of the …, 2021 - ieeexplore.ieee.org
As one of the key communication scenarios in the fifth-generation and also the sixth-
generation (6G) mobile communication networks, ultrareliable and low-latency …

ColO-RAN: Develo** machine learning-based xApps for open RAN closed-loop control on programmable experimental platforms

M Polese, L Bonati, S D'Oro, S Basagni… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Cellular networks are undergoing a radical transformation toward disaggregated, fully
virtualized, and programmable architectures with increasingly heterogeneous devices and …

Federated learning-empowered mobile network management for 5G and beyond networks: From access to core

J Lee, F Solat, TY Kim, HV Poor - … Communications Surveys & …, 2024 - ieeexplore.ieee.org
The fifth generation (5G) and beyond wireless networks are envisioned to provide an
integrated communication and computing platform that will enable multipurpose and …

[HTML][HTML] Deep learning for network traffic monitoring and analysis (NTMA): A survey

M Abbasi, A Shahraki, A Taherkordi - Computer communications, 2021 - Elsevier
Modern communication systems and networks, eg, Internet of Things (IoT) and cellular
networks, generate a massive and heterogeneous amount of traffic data. In such networks …

Deep learning in mobile and wireless networking: A survey

C Zhang, P Patras, H Haddadi - IEEE Communications surveys …, 2019 - ieeexplore.ieee.org
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …

Deep learning for intelligent wireless networks: A comprehensive survey

Q Mao, F Hu, Q Hao - IEEE Communications Surveys & …, 2018 - ieeexplore.ieee.org
As a promising machine learning tool to handle the accurate pattern recognition from
complex raw data, deep learning (DL) is becoming a powerful method to add intelligence to …

Thirty years of machine learning: The road to Pareto-optimal wireless networks

J Wang, C Jiang, H Zhang, Y Ren… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Future wireless networks have a substantial potential in terms of supporting a broad range of
complex compelling applications both in military and civilian fields, where the users are able …

Deep learning with long short-term memory for time series prediction

Y Hua, Z Zhao, R Li, X Chen, Z Liu… - IEEE Communications …, 2019 - ieeexplore.ieee.org
Time series prediction can be generalized as a process that extracts useful information from
historical records and then determines future values. Learning long-range dependencies …