Traffic prediction-enabled energy-efficient dynamic computing resource allocation in cran based on deep learning
Y Fu, X Wang - IEEE Open Journal of the Communications …, 2022 - ieeexplore.ieee.org
Due to the greatly increased bandwidth of 5G networks compared with that of 4G networks,
the power consumption brought by baseband signal processing of 5G networks is much …
the power consumption brought by baseband signal processing of 5G networks is much …
Deep reinforcement learning based dynamic resource allocation in cloud radio access networks
Cloud radio access network (C-RAN) is a promising architecture to fulfill the ever-increasing
resource demand in telecommunication networks. In C-RAN, a base station is decoupled …
resource demand in telecommunication networks. In C-RAN, a base station is decoupled …
Deep mobile traffic forecast and complementary base station clustering for C-RAN optimization
The increasingly growing data traffic has posed great challenges for mobile operators to
increase their data processing capacity, which incurs a significant energy consumption and …
increase their data processing capacity, which incurs a significant energy consumption and …
Convolutional neural network-based deep Q-network (CNN-DQN) resource management in cloud radio access network
The recent surge of mobile subscribers and user data traffic has accelerated the
telecommunication sector towards the adoption of the fifth-generation (5G) mobile networks …
telecommunication sector towards the adoption of the fifth-generation (5G) mobile networks …
Resource allocation for joint energy and spectral efficiency in cloud radio access network based on deep reinforcement learning
The rapid increase of user data traffic demand has promoted the telecommunication sector
toward adopting a new generation, that is, fifth‐generation (5G). Cloud radio access network …
toward adopting a new generation, that is, fifth‐generation (5G). Cloud radio access network …
Energy-efficient and QoS guaranteed BBU aggregation in CRAN based on heuristic-assisted deep reinforcement learning
M Zhu, J Gu, T Shen, C Shi… - Journal of Lightwave …, 2021 - ieeexplore.ieee.org
The surging mobile traffic poses serious challenges for mobile operators, one of which is the
unsustainable growth caused by the high energy consumption of the massively deployed …
unsustainable growth caused by the high energy consumption of the massively deployed …
Machine learning adaptive computational capacity prediction for dynamic resource management in C-RAN
R Guerra-Gomez, S Ruiz-Boque… - IEEE …, 2020 - ieeexplore.ieee.org
Efficient computational resource management in 5G Cloud Radio Access Network (C-RAN)
environments is a challenging problem because it has to account simultaneously for …
environments is a challenging problem because it has to account simultaneously for …
Dynamic resource prediction and allocation in C-RAN with edge artificial intelligence
Artificial intelligence is one of the important technologies for industrial applications, but it
needs a lot of computing resources and sensing data to support. Therefore, big data …
needs a lot of computing resources and sensing data to support. Therefore, big data …
Double deep Q-network-based energy-efficient resource allocation in cloud radio access network
Cloud radio access network (CRAN) has been shown as an effective means to boost
network performance. Such gain stems from the intelligent management of remote radio …
network performance. Such gain stems from the intelligent management of remote radio …
Data-driven C-RAN optimization exploiting traffic and mobility dynamics of mobile users
The surging traffic volumes and dynamic user mobility patterns pose great challenges for
cellular network operators to reduce operational costs and ensure service quality. Cloud …
cellular network operators to reduce operational costs and ensure service quality. Cloud …