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Joint User Association and Energy Aware Routing for Green Small Cell mmWave Backhaul Networks
Dept. of Network Engineering, UPC - BarcelonaTECH, Spain.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. (Distributed systems and communications, DISCO)ORCID iD: 0000-0002-9446-8143
Dept. of Computer Engineering, Gachon University, S.Korea.
2017 (English)In: 2017 IEEE Wireless Communication and Networking Conference (WCNC), Proceedings, San Francisco, USA: IEEE conference proceedings, 2017Conference paper, Published paper (Refereed)
Abstract [en]

A dense deployment of small cells is one of the key characteristics envisioned for future 5G mobile networks in order to provide the required capacity increase. To cut cabling costs, small cells are foreseen to form multihop topologies using high capacity backhaul wireless links in the mmWave bands. Such small cells are deployed within the coverage area of a macro cell (eNB) to provide localized capacity where needed according to the well known Heterogeneous Network concept (HetNet). However, green networking will be very important because powering on unnecessarily a massive amount of small cells may lead to increased OPEX and CO2 emission. In this paper, we propose an optimization model that minimizes the total power consumption of 5G HetNets deployments while providing the required capacity and coverage. Our model jointly optimizes the user association, routing in the multihop backhaul and decides to power on or off the small cells to serve the user demands. Our numerical evaluation show significant power savings over a large range of traffic demand distributions while keeping the blocking probability low.

Place, publisher, year, edition, pages
San Francisco, USA: IEEE conference proceedings, 2017.
Keyword [en]
5G mobile communication, air pollution, optimisation, probability, telecommunication network routing, telecommunication power management
National Category
Computer Science Telecommunications
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-64780DOI: 10.1109/WCNC.2017.7925706ISBN: 978-1-5090-4184-8 (print)ISBN: 978-1-5090-4183-1 (electronic)OAI: oai:DiVA.org:kau-64780DiVA: diva2:1152510
Conference
Wireless Communications and Networking Conference (WCNC), 2017 IEEE San Francisco, CA, USA
Projects
SOCRA (4840)
Funder
Knowledge Foundation
Available from: 2017-10-25 Created: 2017-10-25 Last updated: 2017-11-22Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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