Cellular traffic load prediction with LSTM and Gaussian process regression
Accurate cellular traffic load prediction is a pre-requisite for efficient and automatic network
planning and management. Considering diverse users' activities at different locations and …
planning and management. Considering diverse users' activities at different locations and …
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 …
Time-wise attention aided convolutional neural network for data-driven cellular traffic prediction
Recurrent neural network (RNN) based models are widely adopted to capture temporal
dependencies in the state-of-the-art approaches for cellular traffic prediction. However, RNN …
dependencies in the state-of-the-art approaches for cellular traffic prediction. However, RNN …
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 …
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 …
Cellular traffic prediction and classification: A comparative evaluation of LSTM and ARIMA
Prediction of user traffic in cellular networks has attracted profound attention for improving
the reliability and efficiency of network resource utilization. In this paper, we study the …
the reliability and efficiency of network resource utilization. In this paper, we study the …
Deep convolutional LSTM network-based traffic matrix prediction with partial information
P Le Nguyen, Y Ji - 2019 IFIP/IEEE Symposium on Integrated …, 2019 - ieeexplore.ieee.org
Accurate prediction of the future network traffic plays an important role in various network
problems (eg traffic engineering, capacity planning, quality of service provisioning, etc.) …
problems (eg traffic engineering, capacity planning, quality of service provisioning, etc.) …
Deeptp: An end-to-end neural network for mobile cellular traffic prediction
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 …
due to the popularity of mobile devices. While accurate traffic prediction becomes extremely …
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 …
Mobile traffic prediction from raw data using LSTM networks
Predictive analysis on mobile network traffic is becoming of fundamental importance for the
next generation cellular network. Proactively knowing the user demands, allows the system …
next generation cellular network. Proactively knowing the user demands, allows the system …