Cluster-Based Dynamic FBSs On/Off Scheme in Heterogeneous Cellular Networks

Huang, Xiaoge; Tang, She; Zhang, Dongyu; Chen, Qianbin

doi:10.1007/978-3-030-06161-6_32

Cited by 2 publications

(2 citation statements)

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“…A cluster-based femto BSs switching scheme to maximize the EE of a HetNet was developed in [39], wherein semidefinite programming based correlation clustering algorithm was used to determine the cluster with minimum EE as well as the number of femto BSs to switch off within the cluster while considering load balancing and probability of outage. Similarly, in [14], a cluster-based cell switching scheme for EE optimization in ultra dense SBS network was proposed while considering the user QoS and inter-cell interference.…”

Section: Related Workmentioning

confidence: 99%

“…Different from previous works in [14], [39], [40] where a single type of SBS is deployed, in this work, we consider a UDHN deployment where different types of SBSs (remote radio head (RRH), micro, pico, and femto BSs) are deployed under the coverage of the macro BSs (MBSs). Moreover, unlike the previous works [14], [39], [40] where a SBS is selected as the cluster head and is responsible for controlling the switching off/on of other SBSs, here the MBSs are responsible for controlling the switching off/on of the different SBSs because it has more global information about all the SBSs under its coverage. Also, we consider a scenario where horizontal traffic offloading is not always possible, as a result, vertical traffic offloading is employed in this work.…”

Section: Related Workmentioning

confidence: 99%

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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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Section: Related Workmentioning

confidence: 99%