STEP: A spatio-temporal fine-granular user traffic prediction system for cellular networks
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 …
telecommunication services in cellular networks and attract much attention, they have been …
Spatial-temporal aggregation graph convolution network for efficient mobile cellular traffic prediction
Accurate cellular traffic prediction is challenging due to the complex spatial topology of
cellular network and the dynamic temporal feature of mobile traffic. To overcome these …
cellular network and the dynamic temporal feature of mobile traffic. To overcome these …
Cellular traffic prediction via deep state space models with attention mechanism
Cellular traffic prediction is of great importance for operators to manage network resources
and make decisions. Traffic is highly dynamic and influenced by many exogenous factors …
and make decisions. Traffic is highly dynamic and influenced by many exogenous factors …
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 …
Spatial-temporal attention-convolution network for citywide cellular traffic prediction
Cellular traffic prediction plays an important role in network management and resource
utilization. However, due to the high nonlinearity and dynamic spatial-temporal correlation, it …
utilization. However, due to the high nonlinearity and dynamic spatial-temporal correlation, it …
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 …
Large-scale cellular traffic prediction based on graph convolutional networks with transfer learning
X Zhou, Y Zhang, Z Li, X Wang, J Zhao… - Neural Computing and …, 2022 - Springer
Intelligent cellular traffic prediction is very important for mobile operators to achieve resource
scheduling and allocation. In reality, people often need to predict very large scale of cellular …
scheduling and allocation. In reality, people often need to predict very large scale of cellular …
MVSTGN: A multi-view spatial-temporal graph network for cellular traffic prediction
Timely and accurate cellular traffic prediction is difficult to achieve due to the complex spatial-
temporal characteristics of cellular traffic. The latest approaches mainly aim to model local …
temporal characteristics of cellular traffic. The latest approaches mainly aim to model local …
Cellular traffic prediction: a deep learning method considering dynamic nonlocal spatial correlation, self-attention, and correlation of spatiotemporal feature fusion
Z Rao, Y Xu, S Pan, J Guo, Y Yan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Cellular traffic prediction will play a key role in the deployment of future smart cities.
Although the current traffic prediction methods based on deep learning show better …
Although the current traffic prediction methods based on deep learning show better …
Cellular traffic prediction using recurrent neural networks
Autonomous network traffic prediction will be a key feature in beyond 5G networks. In the
past, researchers have used statistical methods such as Auto Regressive Integrated Moving …
past, researchers have used statistical methods such as Auto Regressive Integrated Moving …