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Joint User Association and Backhaul Routing for Green 5G Mesh Millimeter Wave Backhaul Networks
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013).ORCID-id: 0000-0001-9309-0524
UPC BarcelonaTECH, Barcelona Spain.
Karlstads universitet, Fakulteten för ekonomi, kommunikation och IT, Centrum för HumanIT. Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (from 2013). (DISCO)ORCID-id: 0000-0002-9446-8143
2017 (engelsk)Inngår i: Proceedings Of The 20Th Acm International Conference On Modelling, Analysis And Simulation Of Wireless And Mobile Systems, Association for Computing Machinery (ACM), 2017, s. 179-186Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
Association for Computing Machinery (ACM), 2017. s. 179-186
HSV kategori
Forskningsprogram
Datavetenskap
Identifikatorer
URN: urn:nbn:se:kau:diva-69109DOI: 10.1145/3127540.3127560ISI: 000440745600025ISBN: 978-1-4503-5164-5 (tryckt)OAI: oai:DiVA.org:kau-69109DiVA, id: diva2:1246341
Konferanse
20th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM)21-25 Nov 2017
Tilgjengelig fra: 2018-09-07 Laget: 2018-09-07 Sist oppdatert: 2019-11-13bibliografisk kontrollert

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