Cooperation-enabled energy efficient base station management for dense small cell networks

Chen, Yawen; Wen, Xiangming; Lu, Zhaoming; Shao, Hua; Jing, Wenpeng

doi:10.1007/s11276-016-1234-y

Cited by 8 publications

(2 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The deep plus opportunistic methods were put forward by the authors in Reference 33 to identify the optimum number of SBS and radio wires that ought to be turned off in the dense Het‐Nets. As per the methods for profound sleep, SBSs with nearly zero or minimal load is turned off thus inhabiting the mode of deep sleep throughout a predefined time.…”

Section: Related Workmentioning

confidence: 99%

A new method of hybrid optimization of small cell range development and density for energy efficient ultra‐dense networks

Sidiq

Sheikh

Mustafa

et al. 2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

Ultra-dense networks (UDNs) which comprise of small and macro cells, are considered the principal solution for increasing demands of data. However, making energy efficient networks will be a challenge for researchers. In this article, a hybrid optimization technique is proposed to enhance the energy efficiency (EE) of the UDNs, considering the user correlation and hybrid optimization of the density and transmitting power of the small-cell-base-station (SBS). More precisely, the problem framed is a problem of convex-linear programming and hence is divided into two sub-problems: cell correlation and hybrid optimization. The expression for the EE of the system is derived in the closed-form as a factor of the density of SBSs and small cell-range-development (CRD) bias dependent on the Poisson point process (PPP) followed by the sequential-search-algorithm to improve the small CRD bias and SBS density correspondingly. Additionally, to realize hybrid optimization of the small CRD bias and density of SBSs, a heuristic algorithm is put forward to accomplish the EE of the system. It is revealed from the simulation outcomes that the proposed small CRD bias and SBS density hybrid optimization significantly enhances the EE of the system with low computational intricacy.

show abstract

Section: Related Workmentioning

confidence: 99%

A new method of hybrid optimization of small cell range development and density for energy efficient ultra‐dense networks

Sidiq

Sheikh

Mustafa

et al. 2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…In [25] throughput and EE performance is studied in a separation architecture with files cached at the BSs and limited backhaul infrastructure. Furthermore, in [26] sleeping strategies are proposed for a separation architecture in which small cell BSs form cooperative clusters to provide high data services. Also in [27] the effect of BS sleeping on the EE of a small cell BS belonging to separation architecture and the user-perceived delay is studied and optimal energy saving policies are designed under the constraint of mean delay for different wake up schemes.…”

Section: Introductionmentioning

confidence: 99%

Energy saving in a 5G separation architecture under different power model assumptions

Fisusi

Grace

Mitchell

2017

Computer Communications

View full text Add to dashboard Cite

In this paper, a framework is developed to study the impact of different power model assumptions on energy saving in a 5G separation architecture comprising high power Base Stations (BSs) responsible for coverage, and low power, small cell BSs handling data transmission. Starting with a linear power model function, the achievable energy saving are derived over short timescales by operating small cell BSs in low power states rather than higher power states (termed Low Power State Saving (LPSS) gains) for single and multiple BS scenarios. It is shown how energy saving varies with different power model assumptions over long timescales in accordance with short timescale LPSS. Simulation results show that energy saving in the separation architecture varies across the six power models examined as a function of model-specific significant LPSS state changes. Furthermore, it is shown that if the architecture is based on existing small cell BSs modelled by state-of-the-art (SotA) power models, energy saving will be mainly dependent on sleep state operation. Whereas, if it is based on future BSs modelled by visionary power models, both sleep and idle state operations provide energy saving gains. Moreover, with future BSs, energy saving of up to 42% is achievable when idle state overhead is considered, while a higher saving is possible otherwise.

show abstract

Adaptive energy-efficient small cell sleeping and zooming in heterogeneous cellular networks

2021

View full text Add to dashboard Cite

Cooperation-enabled energy efficient base station management for dense small cell networks

Cited by 8 publications

References 29 publications

A new method of hybrid optimization of small cell range development and density for energy efficient ultra‐dense networks

A new method of hybrid optimization of small cell range development and density for energy efficient ultra‐dense networks

Energy saving in a 5G separation architecture under different power model assumptions

Adaptive energy-efficient small cell sleeping and zooming in heterogeneous cellular networks

Contact Info

Product

Resources

About