Afzal, A, Zaidi, SAR, McLernon, DC et al. (2 more authors) (2017) M2M meets D2D: Harnessing D2D Interfaces for the Aggregation of M2M Data. In: 2017 IEEE International Conference on Communications. IEEE ICC'17: Bridging People, Communities, and Cultures, 21-25 May 2017, Paris, France. IEEE ISBN 978-1-4673-8999-0
Abstract
Direct device-to-device (D2D) communication presents as an effective technique to reduce the load at the base station (BS) while ensuring reliable localized communication. In this paper, we propose a large-scale M2M data Aggregation and Trunking (MAT) scheme, whereby the user equipments (UEs) aggregate M2M data from the nearby MTDs and trunk this data along with their own data to the BS in the cellular uplink. We develop a comprehensive stochastic geometry framework by considering a Poisson hard sphere model for UE coverage. The main motivation of this model is to capture the fact that a UE can gather data from short range, low-power MTDs located only in its close proximity while ensuring that an MTD is associated to at most one UE. We explore the inherent trade-off between the time reserved for aggregation and successful trunking of data to the BS and compare our results with the baseline case where no aggregation mechanism is used. We show that while the baseline case of connecting a bulk of MTDs directly with the BS is prohibitive, MAT scheme can efficiently gather data from selected MTDs in a distributed manner.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2017, 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. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Machine-to-machine communications, Device-to-device communication, Data aggregation, Power control, Cellular networks, Mobile computing |
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) |
Funding Information: | Funder Grant number EPSRC EP/P511341/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Feb 2017 13:35 |
Last Modified: | 15 Sep 2017 01:53 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ICC.2017.7997135 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:112748 |