Hayajneh, A, Zaidi, SAR, McLernon, DC et al. (1 more author) (2016) Drone Empowered Small Cellular Disaster Recovery Networks for Resilient Smart Cities. In: 2016 IEEE International Conference on Sensing, Communication and Networking (SECON Workshops). SECON 2016, 27-30 Jun 2016, London, UK. IEEE ISBN 978-1-5090-2429-2
Abstract
Resilient communication networks, which can continue operations even after a calamity, will be a central feature of future smart cities. Recent proliferation of drones propelled by the availability of cheap commodity hardware presents a new avenue for provisioning such networks. In particular, with the advent of Google’s Sky Bender and Facebook’s internet drone, drone empowered small cellular networks (DSCNs) are no longer fantasy. DSCNs are attractive solution for public safety networks because of swift deployment capability and intrinsic network reconfigurability. While DSCNs have received some attention in the recent past, the design space of such networks has not been extensively traversed. In particular, co-existence of such networks with an operational ground cellular network in a post-disaster situation has not been investigated. Moreover, design parameters such as optimal altitude and number of drone base stations, etc., as a function of destroyed base stations, propagation conditions, etc., have not been explored. In order to address these design issues, we present a comprehensive statistical framework which is developed from stochastic geometric perspective. We then employ the developed framework to investigate the impact of several parametric variations on the performance of the DSCNs. Without loss of any generality, in this article, the performance metric employed is coverage probability of a down-link mobile user. It is demonstrated that by intelligently selecting the number of drones and their corresponding altitudes, ground users coverage can be significantly enhanced. This is attained without incurring significant performance penalty to the mobile users which continue to be served from operating ground infrastructure.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2016, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Drone, Public safety, Stochastic geometry, Unmanned aerial vehicles, Coverage probability, Optimization, Heterogeneous networks |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Sep 2016 15:44 |
Last Modified: | 17 Apr 2017 16:07 |
Published Version: | https://doi.org/10.1109/SECONW.2016.7746806 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/SECONW.2016.7746806 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:104809 |