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Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks

Because of the limited resources on radio access channels of third generation partnership projection (3GPP) network, one of the most challenging tasks posted by 3GPP cellular-based machine type communications (MTC) is congestion due to massive requests for connection to radio access network (RAN). I...

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Detalles Bibliográficos
Autores principales: Lu, Zhaoming, Pan, Qi, Wang, Luhan, Wen, Xiangming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5147883/
https://www.ncbi.nlm.nih.gov/pubmed/27936011
http://dx.doi.org/10.1371/journal.pone.0167380
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author Lu, Zhaoming
Pan, Qi
Wang, Luhan
Wen, Xiangming
author_facet Lu, Zhaoming
Pan, Qi
Wang, Luhan
Wen, Xiangming
author_sort Lu, Zhaoming
collection PubMed
description Because of the limited resources on radio access channels of third generation partnership projection (3GPP) network, one of the most challenging tasks posted by 3GPP cellular-based machine type communications (MTC) is congestion due to massive requests for connection to radio access network (RAN). In this paper, an overload control algorithm in 3GPP RAN is proposed, which proactively disperses the simultaneous access attempts in evenly distributed time window. Through periodic reservation strategy, massive access requests of MTC devices are dispersed in time, which reduces the probability of confliction of signaling. By the compensation and prediction mechanism, each device can communicate with MTC server with dynamic load of air interface. Numerical results prove that proposed method makes MTC applications friendly to 3GPP cellular network.
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spelling pubmed-51478832016-12-28 Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks Lu, Zhaoming Pan, Qi Wang, Luhan Wen, Xiangming PLoS One Research Article Because of the limited resources on radio access channels of third generation partnership projection (3GPP) network, one of the most challenging tasks posted by 3GPP cellular-based machine type communications (MTC) is congestion due to massive requests for connection to radio access network (RAN). In this paper, an overload control algorithm in 3GPP RAN is proposed, which proactively disperses the simultaneous access attempts in evenly distributed time window. Through periodic reservation strategy, massive access requests of MTC devices are dispersed in time, which reduces the probability of confliction of signaling. By the compensation and prediction mechanism, each device can communicate with MTC server with dynamic load of air interface. Numerical results prove that proposed method makes MTC applications friendly to 3GPP cellular network. Public Library of Science 2016-12-09 /pmc/articles/PMC5147883/ /pubmed/27936011 http://dx.doi.org/10.1371/journal.pone.0167380 Text en © 2016 Lu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lu, Zhaoming
Pan, Qi
Wang, Luhan
Wen, Xiangming
Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks
title Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks
title_full Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks
title_fullStr Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks
title_full_unstemmed Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks
title_short Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks
title_sort overload control for signaling congestion of machine type communications in 3gpp networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5147883/
https://www.ncbi.nlm.nih.gov/pubmed/27936011
http://dx.doi.org/10.1371/journal.pone.0167380
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