Data-driven Energy Efficiency Modelling in Large-scale Networks: An Expert Knowledge and ML-based Approach

D López-Pérez, A De Domenico… - … Machine Learning in …, 2024 - ieeexplore.ieee.org
The energy consumption of mobile networks poses a critical challenge. Mitigating this
concern necessitates the deployment and optimization of network energy-saving solutions …

Data-driven energy conservation in cellular networks: A systems approach

G Premsankar, G Piao, PK Nicholson… - … on Network and …, 2021 - ieeexplore.ieee.org
The energy consumption of mobile networks is already substantial nowadays, and only
expected to further increase with the roll-out of 5G. Base stations are the key elements in this …

Intelligent RAN Power Saving using Balanced Model Training in Cellular Networks

V Singh, M Gupta, C Maciocco - 2022 20th International …, 2022 - ieeexplore.ieee.org
optimizing power consumption of 5G systems and next generation technology deployments
is a critical problem. It is essential that the solution for optimizing power consumption takes …

[HTML][HTML] Data driven AI assisted green network design and management

M Masoudi - 2022 - diva-portal.org
The energy consumption of mobile networks is increasing due to an increase in traffic
demands and the number of connected users to the network. To assure the sustainability of …

Use of Machine Learning for energy efficiency in present and future mobile networks

D Sesto-Castilla, E Garcia-Villegas… - 2019 IEEE Wireless …, 2019 - ieeexplore.ieee.org
Given the current evolution trends in mobile cellular networks, which is approaching us
towards the future 5G paradigm, novel techniques for network management are in the …

Edge-distributed coordinated hyper-parameter search for energy saving SON use-case

H Farooq, J Forgeat, S Bothe, M Bouton… - 2022 IEEE …, 2022 - ieeexplore.ieee.org
Energy Efficient operation of ultra-dense hetero-geneous network deployments is a big
challenge for mobile networks. AI-assisted energy saving is one of the potential self …

Reinforcement learning for automated energy efficient mobile network performance tuning

D Corcoran, P Kreuger, M Boman - 2021 17th International …, 2021 - ieeexplore.ieee.org
Modern mobile networks are increasingly complex from a resource management
perspective, with diverse combinations of software, infrastructure elements and services that …

[PDF][PDF] Network Prediction for Energy-Aware Transmission in Mobile Applications

RS Kalyanaraman, Y Xiao, A Ylä-Jääski - International Journal on …, 2010 - Citeseer
Network parameters such as signal-to-noise-ratio (SNR), throughput, and packet loss rate
can be used for measuring the wireless network performance which highly depends on the …

Modeling energy consumption of mobile radio networks: An operator perspective

A Capone, S D'Elia, I Filippini… - IEEE Wireless …, 2017 - ieeexplore.ieee.org
The exponential growth of mobile traffic is forcing operators to quickly increase the capacity
of their networks by means of new technologies and advanced architectures. This capacity …

Processing ANN traffic predictions for RAN energy efficiency

G Vallero, D Renga, M Meo… - Proceedings of the 23rd …, 2020 - dl.acm.org
The field of networking, like many others, is experiencing a peak of interest in the use of
Machine Learning (ML) algorithms. In this paper, we focus on the application of ML tools to …