Wireless traffic prediction with scalable Gaussian process: Framework, algorithms, and verification

Y Xu, F Yin, W Xu, J Lin, S Cui - IEEE Journal on Selected …, 2019 - ieeexplore.ieee.org
The cloud radio access network (C-RAN) is a promising paradigm to meet the stringent
requirements of the fifth generation (5G) wireless systems. Meanwhile, the wireless traffic …

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 …

The learning and prediction of application-level traffic data in cellular networks

R Li, Z Zhao, J Zheng, C Mei, Y Cai… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Traffic learning and prediction is at the heart of the evaluation of the performance of
telecommunications networks and attracts a lot of attention in wired broadband networks …

The prediction analysis of cellular radio access network traffic: From entropy theory to networking practice

R Li, Z Zhao, X Zhou, J Palicot… - IEEE Communications …, 2014 - ieeexplore.ieee.org
Although the research on traffic prediction is an established field, most existing works have
been carried out on traditional wired broadband networks and rarely shed light on cellular …

Spatio-temporal wireless traffic prediction with recurrent neural network

C Qiu, Y Zhang, Z Feng, P Zhang… - IEEE Wireless …, 2018 - ieeexplore.ieee.org
Accurate prediction of user traffic in cellular networks is crucial to improve the system
performance in terms of energy efficiency and resource utilization. However, existing work …

Deeptp: An end-to-end neural network for mobile cellular traffic prediction

J Feng, X Chen, R Gao, M Zeng, Y Li - IEEE Network, 2018 - ieeexplore.ieee.org
The past 10 years have witnessed the rapid growth of global mobile cellular traffic demands
due to the popularity of mobile devices. While accurate traffic prediction becomes extremely …

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 …

Traffic prediction using multifaceted techniques: A survey

S George, AK Santra - Wireless Personal Communications, 2020 - Springer
Road transportation is the largest and complex nonlinear entity of the traffic management
system. Accurate prediction of traffic-related information is necessary for an effective …

A meta-learning scheme for adaptive short-term network traffic prediction

Q He, A Moayyedi, G Dán… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
Network traffic prediction is a fundamental prerequisite for dynamic resource provisioning in
wireline and wireless networks, but is known to be challenging due to non-stationarity and …

STEP: A spatio-temporal fine-granular user traffic prediction system for cellular networks

L Yu, M Li, W Jin, Y Guo, Q Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
While traffic modeling and prediction are at the heart of providing high-quality
telecommunication services in cellular networks and attract much attention, they have been …