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Optimal Steerable mmWave Mesh Backhaul Reconfiguration
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-4961-5087
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). Stevens Institute of Technology, USA.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-9446-8143
2018 (English)In: 2018 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), IEEE, 2018Conference paper, Published paper (Refereed)
Abstract [en]

Future 5G mobile networks will require increased backhaul (BH) capacity to connect a massive amount of high capacity small cells (SCs) to the network. Because having an optical connection to each SC might be infeasible, mmWave-based (e.g. 60 GHz) BH links are an interesting alternative due to their large available bandwidth. To cope with the increased path loss, mmWave links require directional antennas that should be able to direct their beams to different neighbors, to dynamically change the BH topology, in case new nodes are powered on/off or the traffic demand has changed. Such BH adaptation needs to be orchestrated to minimize the impact on existing traffic.This paper develops a Software-defined networking-based framework that guides the optimal reconfiguration of mesh BH networks composed by mmWave links, where antennas need to be mechanically aligned.By modelling the problem as a Mixed Integer Linear Program (MILP), its solution returns the optimal ordering of events necessary to transition between two BH network configurations. The model creates backup paths whenever it is possible, while minimizing the packet loss of ongoing flows. A numerical evaluation with different topologies and traffic demands shows that increasing the number of BH interfaces per SC from 2 to 4 can decrease the total loss by more than 50%. Moreover, when increasing the total reconfiguration time, additional backup paths can be created, consequently reducing the reconfiguration impact on existing traffic.

Place, publisher, year, edition, pages
IEEE, 2018.
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-69436ISI: 000465774303123ISBN: 978-1-5386-4727-1 (print)OAI: oai:DiVA.org:kau-69436DiVA, id: diva2:1252653
Conference
IEEE Global Communications Conference (GLOBECOM)
Projects
Socra, 4840
Funder
Knowledge FoundationAvailable from: 2018-10-02 Created: 2018-10-02 Last updated: 2019-06-11
In thesis
1. 5G Backhauling with Software-defined Wireless Mesh Networks
Open this publication in new window or tab >>5G Backhauling with Software-defined Wireless Mesh Networks
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Current technological advances have caused an exponential growth of the number of mobile Internet-connected devices, along with their respective traffic demands. To cope with this increase of traffic demands, fifth generation (5G) network architectures will need to provide multi-gigabit capacity at the access base stations (BSs), through the deployment of ultra-dense small cells (SCs) operating with millimeter-wave (mmWave) frequencies, e.g. 60 GHz. To connect the BSs to the core network, a robust and high capacity backhaul infrastructure is required. As it is unfeasible to connect all the SCs through optical fiber links, a solution for the future 5G backhaul relies on the usage of mmWave frequencies to interconnect the SCs, forming multi-hop wireless mesh topologies. In this thesis, we explore the application of the Software-defined Networking (SDN) paradigm for the management of a SC wireless backhaul. With SDN, the data and control planes are separated and the network management is done by a centralized controller entity that has a global network view. To that end, we provide multiple contributions. Firstly, we provide an SDN-based architecture to manage SC backhaul networks, which include an out-of-band Long Term Evolution (LTE) control channel and where we consider aspects such as energy efficiency, resiliency and flexible backhaul operation. Secondly, we demonstrate the benefit of the wireless backhaul configuration using the SDN controller, which can be used to improve the wireless resource allocation and provide resiliency mechanisms in the network. Finally, we investigate how a SC mesh backhaul can be optimally reconfigured between different topologies, focusing on minimizing the network disruption during the reconfiguration.

Abstract [en]

The growth of mobile devices, along with their traffic demands, is expected to saturate the current mobile networks soon. To cope with such demand increase, fifth generation (5G) network architectures will need to provide multi-gigabit capacity at the access level, through the deployment of a massive amount of ultra-dense small cells (SCs). To connect the access and core networks, a robust and high capacity backhaul is required. To that end, mmWave links that operate at e.g. 60 GHz, can be used to interconnect the SCs, forming multi-hop wireless mesh topologies.

 

In this thesis, we study the application of the Software-defined Networking (SDN) paradigm for the management of a SC wireless backhaul. Firstly, we provide an SDN-based architecture to manage SC backhaul networks, which includes an out-of-band control channel and where we consider aspects such as energy efficiency, resiliency and flexible backhaul operation. Secondly, we show the benefits of the wireless backhaul configuration using the SDN controller, which can be used to improve the wireless resource allocation and provide network resiliency. Finally, we investigate how a SC mesh backhaul can be optimally reconfigured between different topologies, while minimizing the network disruption during the reconfiguration.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2018. p. 95
Series
Karlstad University Studies, ISSN 1403-8099 ; 2018:44
Keywords
SDN, wireless backhaul, heterogeneous networks, mmWave, 5G, resiliency
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-69437 (URN)978-91-7063-881-7 (ISBN)978-91-7063-976-0 (ISBN)
Presentation
2018-10-22, 09:15 (English)
Opponent
Supervisors
Available from: 2018-10-26 Created: 2018-10-02 Last updated: 2018-10-26Bibliographically approved

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Santos, RicardoGhazzai, HakimKassler, Andreas

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