Leveraging intelligence from network CDR data for interference aware energy consumption minimization

A Zoha, A Saeed, H Farooq, A Rizwan… - IEEE Transactions …, 2017 - ieeexplore.ieee.org
Cell densification is being perceived as the panacea for the imminent capacity crunch.
However, high aggregated energy consumption and increased inter-cell interference (ICI) …

Realtime scheduling and power allocation using deep neural networks

S Xu, P Liu, R Wang, SS Panwar - 2019 IEEE Wireless …, 2019 - ieeexplore.ieee.org
With the increasing number of base stations (BSs) and network densification in 5G,
interference management using link scheduling and power control are vital for better …

Radio resource allocation in 5G cellular networks powered by the smart grid and renewable energies

A El Amine - 2019 - theses.fr
The heated 5G network deployment race had begun between competitors to outperform one
another and be the most innovative followed by a rapid progress towards standardization …

Energy optimization in ultra-dense radio access networks via traffic-aware cell switching

M Ozturk, AI Abubakar, JPB Nadas… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
We propose a reinforcement learning-based cell switching algorithm to minimize the energy
consumption in ultra-dense deployments without compromising the quality of service (QoS) …

Energy saving and interference coordination in HetNets using dynamic programming and CEC

JA Ayala-Romero, JJ Alcaraz, J Vales-Alonso - IEEE Access, 2018 - ieeexplore.ieee.org
Energy efficiency in cellular networks has gained great relevance due to the increasing
power supply demands in new generation heterogeneous network (HetNet). On the other …

Deep reinforcement learning for cell on/off energy saving on wireless networks

JS Pujol–Roigl, S Wu, Y Wang… - 2021 IEEE Global …, 2021 - ieeexplore.ieee.org
Increased network traffic demands have led to ex-tremely dense network deployments. This
translates to significant growth in energy consumption at the radio access networks …

Energy-efficient ultra-dense 5G networks: recent advances, taxonomy and future research directions

A Mughees, M Tahir, MA Sheikh, A Ahad - IEEE Access, 2021 - ieeexplore.ieee.org
The global surge of connected devices and multimedia services necessitates increased
capacity and coverage of communication networks. One approach to address the …

Cell on/off parameter optimization for saving energy via reinforcement learning

M Choi, K Kim, H Jang, H Woo… - 2021 IEEE …, 2021 - ieeexplore.ieee.org
Energy cost accounts for a large portion of expenses when operating a cellular mobile
network, and it is expected to increase further to support advanced communication features …

Online learning for energy saving and interference coordination in HetNets

JA Ayala-Romero, JJ Alcaraz… - IEEE Journal on …, 2019 - ieeexplore.ieee.org
In heterogeneous cellular networks (HetNets), switching OFF small cells under low user
traffic periods has been proved to be an effective energy saving strategy. However, this …

Using neural networks to reduce sensor cluster interferences and power consumption in smart cities

P Lynggaard - International Journal of Sensor Networks, 2020 - inderscienceonline.com
In the future smart cities, billions of communicating Internet of Things (IoT) devices are
expected which communicate wirelessly in the limited spectrum offered by 5G and long …