On reducing energy cost consumption in heterogeneous cellular networks using optimal time constraint algorithm

The increasing data demand in recent years has resulted in a considerable rise in heterogeneous cellular network energy usage. Advances in heterogeneous cellular networks with renewable energy supplied from base stations offer the cellular communications sector interesting options. Rising energy con...

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Veröffentlicht in:Optik (Stuttgart) Jg. 270; S. 170008
Hauptverfasser: Kalpana, V., Mishra, Divyendu Kumar, Chanthirasekaran, K., Haldorai, Anandakumar, Nath, Srigitha.S., Saraswat, Bal Krishna
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier GmbH 01.11.2022
Schlagworte:
Cellular communication
Energy cost optimization
Heterogeneous Cellular Network
Optimal time constraint algorithm
Heterogeneous Cellular Network
Optimal time constraint algorithm
Cellular communication
Energy cost optimization
ISSN:0030-4026
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Zusammenfassung:The increasing data demand in recent years has resulted in a considerable rise in heterogeneous cellular network energy usage. Advances in heterogeneous cellular networks with renewable energy supplied from base stations offer the cellular communications sector interesting options. Rising energy consumption, fuelled by huge growth in user count as well as usage of data, has emerged as the most pressing challenge for operators in fulfilling cost-cutting and environmental-impact objectives. The use of minimum power relay stations or base stations in conventional microcells is intended to lower the cellular network's total energy usage. This paper examines the reasons, difficulties, and techniques for addressing renewable heterogeneous networks' energy cost reduction issue. Because of the variety of renewable energy and mobile traffic, the issue of reducing energy costs necessitates both spatial and temporal resource allotment optimization. In this paper, we proposed a new technique for reducing the energy consumption cost using the optimal time constraint algorithmic approach. We demonstrate that the proposed method has time as well as space complexity. Experimental simulations on actual databases with synthetic costs are used to confirm the usefulness and efficacy of our method.
ISSN:0030-4026
DOI:10.1016/j.ijleo.2022.170008