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 …

An overview of terahertz antennas

Y He, Y Chen, L Zhang, SW Wong… - China …, 2020 - ieeexplore.ieee.org
The terahertz (THz) antennas, which have features of small size, wide frequency bandwidth
and high data rate, are important devices for transmitting and receiving THz electromagnetic …

Deep transfer learning for intelligent cellular traffic prediction based on cross-domain big data

C Zhang, H Zhang, J Qiao, D Yuan… - IEEE Journal on …, 2019 - ieeexplore.ieee.org
Machine (deep) learning-enabled accurate traffic modeling and prediction is an
indispensable part for future big data-driven intelligent cellular networks, since it can help …

Forecasting network traffic: A survey and tutorial with open-source comparative evaluation

GO Ferreira, C Ravazzi, F Dabbene… - IEEE …, 2023 - ieeexplore.ieee.org
This paper presents a review of the literature on network traffic prediction, while also serving
as a tutorial to the topic. We examine works based on autoregressive moving average …

Dual attention-based federated learning for wireless traffic prediction

C Zhang, S Dang, B Shihada… - IEEE INFOCOM 2021 …, 2021 - ieeexplore.ieee.org
Wireless traffic prediction is essential for cellular networks to realize intelligent network
operations, such as load-aware resource management and predictive control. Existing …

Long-term mobile traffic forecasting using deep spatio-temporal neural networks

C Zhang, P Patras - Proceedings of the eighteenth ACM international …, 2018 - dl.acm.org
Forecasting with high accuracy the volume of data traffic that mobile users will consume is
becoming increasingly important for precision traffic engineering, demand-aware network …

Artificial intelligence for satellite communication: A review

F Fourati, MS Alouini - Intelligent and Converged Networks, 2021 - ieeexplore.ieee.org
Satellite communication offers the prospect of service continuity over uncovered and under-
covered areas, service ubiquity, and service scalability. However, several challenges must …

Big data driven marine environment information forecasting: a time series prediction network

J Wen, J Yang, B Jiang, H Song… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The continuous development of industry big data technology requires better computing
methods to discover the data value. Information forecast, as an important part of data mining …

DeepCog: Cognitive network management in sliced 5G networks with deep learning

D Bega, M Gramaglia, M Fiore… - … -IEEE conference on …, 2019 - ieeexplore.ieee.org
Network slicing is a new paradigm for future 5G networks where the network infrastructure is
divided into slices devoted to different services and customized to their needs. With this …