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SDN enabled resiliency in LTE assisted small cell mmWave backhaul networks
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. (Distributed systems and communication, DISCO)ORCID iD: 0000-0001-7358-8675
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Computer Science. (Distributed systems and communication, DISCO)ORCID iD: 0000-0002-9446-8143
2017 (English)In: Innovations in Clouds, Internet and Networks (ICIN), 2017 20th Conference on, IEEE, 2017Conference paper, Published paper (Refereed)
Abstract [en]

As mobile data usage increases dramatically, new architectures and technologies for wireless communication are required. Next generation of mobile networks are expected to be augmented by a massive amount of small cells that will be densely deployed. In order to connect the small cells, new high capacity wireless backhauling technologies are required. A promising solution is to use frequencies in the mmWave band, which allows for much greater capacity due to the massive amount of free spectrum. However, the special characteristics of the mmWave bands such as high path loss and atmospheric absorption lead to unstable links. In this paper, we investigate using Software Defined Networking principles for the operation and control of wireless backhaul networks. We demonstrate how SDN resiliency mechanisms can be used to mitigate disruptive connectivity due to mmWave links frequently failing. For assisting the small cell backhauling, we propose to also use the LTE uplinks of the small cells as backup links, should the mmWave mesh forwarding link break. Our experiments using a network emulator show that using SDN-based local repair mechanisms can significantly reduce the packet loss rate inside the mmWave backhaul mesh, which can be further reduced with an LTE assisted Failover.

Place, publisher, year, edition, pages
IEEE, 2017.
Keyword [en]
cellular radio, Long Term Evolution, millimetre waves, next generation networks, radio links, software defined networking
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-65608DOI: 10.1109/ICIN.2017.7899411OAI: oai:DiVA.org:kau-65608DiVA: diva2:1174249
Conference
The 20th Conference on Innovations in Clouds, Internet and Networks (ICIN), 7-9 March 2017. Paris, France
Available from: 2018-01-15 Created: 2018-01-15 Last updated: 2018-01-15

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