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Joint User Association and Backhaul Routing for Green 5G Mesh Millimeter Wave Backhaul Networks
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0001-9309-0524
UPC BarcelonaTECH, Barcelona Spain.
Karlstad University, Faculty of Economic Sciences, Communication and IT, Centre for HumanIT. Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (DISCO)ORCID iD: 0000-0002-9446-8143
2017 (English)In: Proceedings Of The 20Th Acm International Conference On Modelling, Analysis And Simulation Of Wireless And Mobile Systems, ASSOC COMPUTING MACHINERY, , 2017, p. 179-186Conference paper, Published paper (Refereed)
Abstract [en]

With the advance of fifth generation (5G) networks, network density needs to grow significantly in order to meet the required capacity demands. A massive deployment of small cells may lead to a high cost for providing. ber connectivity to each node. Consequently, many small cells are expected to be connected through wireless links to the umbrella eNodeB, leading to a mesh backhaul topology. This backhaul solution will most probably be composed of high capacity point-to-point links, typically operating in the millimeter wave (mmWave) frequency band due to its massive bandwidth availability. In this paper, we propose a mathematical model that jointly solves the user association and backhaul routing problem in the aforementioned context, aiming at the energy efficiency maximization of the network. Our study considers the energy consumption of both the access and backhaul links, while taking into account the capacity constraints of all the nodes as well as the fulfillment of the service-level agreements (SLAs). Due to the high complexity of the optimal solution, we also propose an energy efficient heuristic algorithm (Joint), which solves the discussed joint problem, while inducing low complexity in the system. We numerically evaluate the algorithm performance by comparing it not only with the optimal solution but also with reference approaches under different traffic load scenarios and backhaul parameters. Our results demonstrate that Joint outperforms the state-of-the-art, while being able to find good solutions, close to optimal, in short time.

Place, publisher, year, edition, pages
ASSOC COMPUTING MACHINERY, , 2017. p. 179-186
Series
PROCEEDINGS OF THE 20TH ACM INTERNATIONAL CONFERENCE ON MODELLING, ANALYSIS AND SIMULATION OF WIRELESS AND MOBILE SYSTEMS (MSWIM'17)
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-69109DOI: 10.1145/3127540.3127560ISI: 000440745600025ISBN: 978-1-4503-5164-5 (print)OAI: oai:DiVA.org:kau-69109DiVA, id: diva2:1246341
Conference
20th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM)21-25 Nov 2017
Available from: 2018-09-07 Created: 2018-09-07 Last updated: 2019-05-27Bibliographically approved

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Agapi, MesodiakakiKassler, Andreas

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