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 …
support billions of mobile users and devices. Powered by artificial intelligence techniques …
Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
[HTML][HTML] Deep learning for network traffic monitoring and analysis (NTMA): A survey
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 …
networks, generate a massive and heterogeneous amount of traffic data. In such networks …
A survey on 5G radio access network energy efficiency: Massive MIMO, lean carrier design, sleep modes, and machine learning
Cellular networks have changed the world we are living in, and the fifth generation (5G) of
radio technology is expected to further revolutionise our everyday lives by enabling a high …
radio technology is expected to further revolutionise our everyday lives by enabling a high …
A deep learning method based on an attention mechanism for wireless network traffic prediction
M Li, Y Wang, Z Wang, H Zheng - Ad Hoc Networks, 2020 - Elsevier
With the rapid development of wireless networks, the self-management and active
adjustment capabilities of base stations have become crucial. The accurate prediction of …
adjustment capabilities of base stations have become crucial. The accurate prediction of …
Big data in forecasting research: a literature review
L Tang, J Li, H Du, L Li, J Wu, S Wang - Big Data Research, 2022 - Elsevier
With the boom in Internet techniques and computer science, a variety of big data have been
introduced into forecasting research, bringing new knowledge and improving prediction …
introduced into forecasting research, bringing new knowledge and improving prediction …
Spatial-temporal cellular traffic prediction for 5G and beyond: A graph neural networks-based approach
During the past decade, Industry 4.0 has greatly promoted the improvement of industrial
productivity by introducing advanced communication and network technologies in the …
productivity by introducing advanced communication and network technologies in the …
Deep learning at the mobile edge: Opportunities for 5G networks
Mobile edge computing (MEC) within 5G networks brings the power of cloud computing,
storage, and analysis closer to the end user. The increased speeds and reduced delay …
storage, and analysis closer to the end user. The increased speeds and reduced delay …
Forecasting network traffic: A survey and tutorial with open-source comparative evaluation
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 …
as a tutorial to the topic. We examine works based on autoregressive moving average …
Predictive deployment of UAV base stations in wireless networks: Machine learning meets contract theory
In this paper, a novel framework is proposed to enable a predictive deployment of
unmanned aerial vehicles (UAVs) as temporary base stations (BSs) to complement ground …
unmanned aerial vehicles (UAVs) as temporary base stations (BSs) to complement ground …