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On the Association of Small Cell Base Stations with UAVs using Unsupervised Learning
National University of Sciences and Technology (NUST), Pakistan.
National University of Sciences and Technology (NUST), Pakistan.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.ORCID iD: 0000-0003-3717-7793
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.ORCID iD: 0000-0003-0873-7827
2019 (English)In: IEEE 89th Vehicular Technology Conference, VTC2019-Spring, Institute of Electrical and Electronics Engineers (IEEE), 2019, article id 8746456Conference paper, Published paper (Refereed)
Abstract [en]

Small cell networks (SCNs) offer a cost-effective coverage solution to wireless applications demanding high data rates. However in SCNs, a challenging problem is the proper management of backhaul links to small cell base stations(SCBSs). To make a good backhaul link, perfect line-of-sight (LoS) communication between the SCBSs and the core network plays a vital role. In this study, we use the idea of employing unmanned aerial vehicles (UAVs) to provide connectivity betweenSCBSs and the core network. We focus on the association of SCBSs with UAVs by considering multiple communication-related factors including data rate limit and available bandwidth resources of the backhaul. In particular, we address the optimum placement of UAVs to serve a maximum number of SCBSswhile considering available resources using the unsupervised k-means algorithm. Numerical results show that the proposed approach outperforms the conventional approach in terms of associatedSCBSs, bandwidth consumption, available link utilization, and sum-rate maximization.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019. article id 8746456
Keywords [en]
Drones, unmanned aerial vehicles (UAVs), small cell base stations, fronthaul/backhaul network, unsupervised learning
National Category
Communication Systems Telecommunications
Identifiers
URN: urn:nbn:se:miun:diva-35732DOI: 10.1109/VTCSpring.2019.8746456Scopus ID: 2-s2.0-85068960845OAI: oai:DiVA.org:miun-35732DiVA, id: diva2:1293491
Conference
IEEE 89th Vehicular Technology Conference, VTC2019-Spring, 5th International Workshop of CorNer: Communication for Networked Smart Cities, Kuala Lumpur, Malaysia, 28 April – 1 May 2019
Funder
Knowledge FoundationAvailable from: 2019-03-05 Created: 2019-03-05 Last updated: 2019-08-13Bibliographically approved

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Mahmood, AamirGidlund, Mikael

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