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    Growing green with improved profit through reduced power consumption in LTE networks

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    Authors
    Kanwal, Kapil
    Safdar, Ghazanfar Ali
    Affiliation
    University of Bedfordshire
    Issue Date
    2017-03-31
    Subjects
    OPEX
    growing green
    CAPEX
    energy saving
    
    Metadata
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    Other Titles
    ICC '17: Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing
    Abstract
    Long Term Evolution (LTE) is well known 4G technology which promises higher data rates. Due to advancements in smart phones and new applications, the user's data requirements have significantly increased. The data hungry users engage radio resources over long periods of time thus resulting into higher energy consumption by Base stations (BSs). Increased energy consumption due to higher data rates directly increases Operational Expenditure (OPEX) thereby ensuing economic and environmental benefits, i.e. profitability and Global Warming. This paper presents detailed performance analysis of our novel joint resources block switching off and bandwidth expansion based energy saving scheme. Our proposed scheme offers 29% energy saving thus results in to decreased CO2 emissions (approximately 1.12 tonnes/ BS) and reduced OPEX thereby enabling mobile vendors to have high profile in Growing Green and help them to improve both environmental and economic aspects. Vendors could enjoy increased profit and stay Green through usage of our energy saving scheme.
    Citation
    Kanwal K, Safdar G (2017) 'Growing green with improved profit through reduced power consumption in LTE networks', Second International Conference on Internet of things, Data and Cloud Computing - Cambridge , Association for Computing Machinery.
    Publisher
    Association for Computing Machinery
    URI
    http://hdl.handle.net/10547/624233
    DOI
    10.1145/3018896.3018910
    Additional Links
    https://dl.acm.org/doi/abs/10.1145/3018896.3018910
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISBN
    9781450347747
    ae974a485f413a2113503eed53cd6c53
    10.1145/3018896.3018910
    Scopus Count
    Collections
    Computing

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