ICE: Intelligent cell brEathing to optimize the utilization of green energy

Tao Han; Nirwan Ansari

doi:10.1109/LCOMM.2012.042312.120486

ICE: Intelligent cell brEathing to optimize the utilization of green energy

Tao Han, Nirwan Ansari

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

64 Scopus citations

Abstract

This letter proposes Intelligent Cell brEathing (ICE) to optimize the utilization of green energy in cellular networks by minimizing the maximal energy depleting rate of the low-power base stations powered by green energy. Minimizing the maximal depleting rate is an NP-hard problem. ICE is thus proposed to achieve low computational complexity. ICE, in each iteration, finds the energy dependent set and the vector of beacon power level decrements for low-power base stations in the set, and then shrinks the coverage area of these base stations by reducing their beacon power levels. The algorithm iterates until the optimal solution is found. ICE balances the energy consumptions among LBSs, enables more users to be served with green energy, and therefore reduces the on-grid energy consumption.

Original language	English (US)
Article number	6189819
Pages (from-to)	866-869
Number of pages	4
Journal	IEEE Communications Letters
Volume	16
Issue number	6
DOIs	https://doi.org/10.1109/LCOMM.2012.042312.120486
State	Published - Jun 2012

All Science Journal Classification (ASJC) codes

Modeling and Simulation
Computer Science Applications
Electrical and Electronic Engineering

Keywords

Energy efficient communications
cellular networks
renewable energy

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10.1109/LCOMM.2012.042312.120486

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title = "ICE: Intelligent cell brEathing to optimize the utilization of green energy",

abstract = "This letter proposes Intelligent Cell brEathing (ICE) to optimize the utilization of green energy in cellular networks by minimizing the maximal energy depleting rate of the low-power base stations powered by green energy. Minimizing the maximal depleting rate is an NP-hard problem. ICE is thus proposed to achieve low computational complexity. ICE, in each iteration, finds the energy dependent set and the vector of beacon power level decrements for low-power base stations in the set, and then shrinks the coverage area of these base stations by reducing their beacon power levels. The algorithm iterates until the optimal solution is found. ICE balances the energy consumptions among LBSs, enables more users to be served with green energy, and therefore reduces the on-grid energy consumption.",

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author = "Tao Han and Nirwan Ansari",

note = "Funding Information: Manuscript received March 6, 2012. The associate editor coordinating the review of this letter and approving it for publication was H. Yomo. The authors are with the Advanced Networking Lab., Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, 07102 USA (e-mail: {th36, nirwan.ansari}@njit.edu). This work was supported in part by NSF under grant no. CNS-1147602. Digital Object Identifier 10.1109/LCOMM.2012.042312.120486",

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AB - This letter proposes Intelligent Cell brEathing (ICE) to optimize the utilization of green energy in cellular networks by minimizing the maximal energy depleting rate of the low-power base stations powered by green energy. Minimizing the maximal depleting rate is an NP-hard problem. ICE is thus proposed to achieve low computational complexity. ICE, in each iteration, finds the energy dependent set and the vector of beacon power level decrements for low-power base stations in the set, and then shrinks the coverage area of these base stations by reducing their beacon power levels. The algorithm iterates until the optimal solution is found. ICE balances the energy consumptions among LBSs, enables more users to be served with green energy, and therefore reduces the on-grid energy consumption.

KW - Energy efficient communications

KW - cellular networks

KW - renewable energy

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ICE: Intelligent cell brEathing to optimize the utilization of green energy

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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