Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/103890
Title: Adaptive power management for wireless base stations in a smart grid environment
Authors: Niyato, Dusit
Lu, Xiao
Wang, Ping
Keywords: DRNTU::Engineering::Computer science and engineering::Computer systems organization
Issue Date: 2012
Source: Niyato, D., Lu, X., & Wang, P. (2012). Adaptive power management for wireless base stations in a smart grid environment. IEEE wireless communications, 19(6), 44-51.
Series/Report no.: IEEE wireless communications
Abstract: The growing concerns of a global environmental change leads to a revolution in the way energy is utilized. In the wireless industry, green wireless communications has recently gained increasing attention and is expected to play a major role in the reduction of electrical power consumption. Actions to promote energy saving of wireless communications with regard to environmental protection are becoming imperative. To this purpose, we study a green communications system model where a wireless base station is provisioned with a combination of a renewable power source and the electrical grid to minimize the cost of power consumption as well as meet the users' demand. More specifically, we focus on adaptive power management for a wireless base station under various uncertainties, including renewable power generation, power price, and wireless traffic load. We believe that demand-side power management solutions based on the studied communication architecture is a major step toward green wireless communications.
URI: https://hdl.handle.net/10356/103890
http://hdl.handle.net/10220/16548
ISSN: 1536-1284
DOI: http://dx.doi.org/10.1109/MWC.2012.6393517
Rights: © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/MWC.2012.6393517].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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