Toward dynamic 3D sectorization using real traffic profile for green 5G cellular networks

Ferhi, Leila Aissaoui; Sethom, Kaouthar; Choubani, Fethi

doi:10.1109/aset.2018.8379863

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…Various methods have been proposed for the optimization of energy consumption in ultra-dense networks (UDN) including antenna muting [5], cell zooming [6], power control [7], sectorization [8], dynamic cell switching operations [9], etc. Among all these methods, dynamic cell switching is the most commonly used approach because it results in the most energy savings, it is easier to implement and it requires minimal changes in the architecture of the network [10]- [12].…”

Section: Introductionmentioning

confidence: 99%

A Lightweight Cell Switching and Traffic Offloading Scheme for Energy Optimization in Ultra-Dense Heterogeneous Networks

Abubakar¹,

Mollel²,

Öztürk³

et al. 2021

Preprint

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One of the major capacity boosters for 5G networks is the deployment of ultra-dense heterogeneous networks (UDHNs). However, this deployment results in tremendous increase in the energy consumption of the network due to the large number of base stations (BSs) involved. In addition to enhanced capacity, 5G networks must also be energy efficient for it to be economically viable and environmentally friendly. Dynamic cell switching is a very common way of reducing the total energy consumption of the network but most of the proposed methods are computationally demanding which makes them unsuitable for application in ultra-dense network deployment with massive number of BSs. To tackle this problem, we propose a lightweight cell switching scheme also known as Threshold-based Hybrid cEll swItching Scheme (THESIS) for energy optimization in UDHNs. The developed approach combines the benefits of clustering and exhaustive search (ES) algorithm to produce a solution whose optimality is close to that of the ES (which is guaranteed to be optimal), but is computationally more efficient than ES and as such can be applied for cell switching in real networks even when their dimension is large. The performance evaluation shows that the THESIS produces a significant reduction in the energy consumption of the UDHN and is able to reduce the complexity of finding a near-optimal solution from exponential to polynomial complexity.

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