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Energy consumption comparison between macro-micro and public femto deployment in a plausible LTE network

Published: 31 May 2011 Publication History

Abstract

We study the energy consumptions of two strategies that increase the capacity of an LTE network: (1) the deployment of redundant macro and micro base stations by the operator at locations where the traffic is high, and (2) the deployment of publicly accessible femto base stations by home users. Previous studies show the deployment of publicly accessible residential femto base stations is considerably more energy efficient; however, the results are proposed using an abstracted model of LTE networks, where the coverage constraint was neglected in the study, as well as some other important physical and traffic layer specifications of LTE networks. We study a realistic scenario where coverage is provided by a set of non-redundant macro-micro base stations and additional capacity is provided by redundant macro-micro base stations or by femto base stations. We quantify the energy consumption of macro-micro and femto deployment strategies by using a simulation of a plausible LTE deployment in a mid-size metropolitan area, based on data obtained from an operator and using detailed models of heterogeneous devices, traffic, and physical layers. The metrics of interest are operator-energy-consumption/total-energy-consumption per unit of network capacity.
For the scenarios we studied, we observe the following: (1) There is no significant difference between operator energy consumption of femto and macro-micro deployment strategies. From the point of view of society, i.e. total energy consumption, macro-micro deployment is even more energy efficient in some cases. This differs from the previous findings, which compared the energy consumption of femto and macro-micro deployment strategies, and found that femto deployment is considerably more energy efficient. (2) The deployment of femto base stations has a positive effect on mobile-terminal energy consumption; however, it is not significant compared to the macro-micro deployment strategy. (3) The energy saving that could be obtained by making macro and micro base stations more energy proportional is much higher than that of femto deployment.

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  1. Energy consumption comparison between macro-micro and public femto deployment in a plausible LTE network

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        e-Energy '11: Proceedings of the 2nd International Conference on Energy-Efficient Computing and Networking
        May 2011
        113 pages
        ISBN:9781450313131
        DOI:10.1145/2318716
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Published: 31 May 2011

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        Author Tags

        1. LTE networks
        2. energy
        3. performance evaluation

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        • (2022)Green Machine Learning Approach for QoS Improvement in Cellular Communications2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA)10.1109/MI-STA54861.2022.9837585(523-528)Online publication date: 23-May-2022
        • (2019)Estimating Base Station Power Consumption Using Regression2019 3rd International Conference on Bio-engineering for Smart Technologies (BioSMART)10.1109/BIOSMART.2019.8734253(1-4)Online publication date: Apr-2019
        • (2016)Chapter 6 Multicellular Heterogeneous NetworksAdvances in Mobile Computing and Communications10.1201/9781315371917-7(205-224)Online publication date: 17-Aug-2016
        • (2016)Exploiting Caching and Multicast for 5G Wireless NetworksIEEE Transactions on Wireless Communications10.1109/TWC.2016.251441815:4(2995-3007)Online publication date: Apr-2016
        • (2016)Greening the Airwaves With Collaborating Mobile Network OperatorsIEEE Transactions on Wireless Communications10.1109/TWC.2015.247878615:1(794-806)Online publication date: 1-Jan-2016
        • (2016)Traffic-aware two-dimensional dynamic network provisioning for energy-efficient cellular systemsTransactions on Emerging Telecommunications Technologies10.1002/ett.287227:3(357-372)Online publication date: 1-Mar-2016
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        • (2014)SC-FDE femtocell energy saving using IB-DFE Interference Cancellation techniques2014 21st International Conference on Telecommunications (ICT)10.1109/ICT.2014.6845133(328-332)Online publication date: May-2014
        • (2014)Interplay between cost, capacity and power consumption in heterogeneous mobile networks2014 21st International Conference on Telecommunications (ICT)10.1109/ICT.2014.6845088(98-102)Online publication date: May-2014
        • (2014)Dynamic Resource Provisioning for Energy Efficiency in Wireless Access Networks: A Survey and an OutlookIEEE Communications Surveys & Tutorials10.1109/COMST.2014.232950516:4(2259-2285)Online publication date: Dec-2015
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