A Traffic Model for Machine-Type Communications Using Spatial Point Processes

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Resumé

A source traffic model for machine-to-machine communications is presented in this paper. We consider a model in which devices operate in a regular mode until they are triggered into an alarm mode by an alarm event. The positions of devices and events are modeled by means of Poisson point processes, where the generated traffic by a given device depends on its position and event positions. We first consider the case where devices and events are static and devices generate traffic according to a Bernoulli process, where we derive the total rate from the devices at the base station. We then extend the model by defining a two-state Markov chain for each device, which allows for devices to stay in alarm mode for a geometrically distributed holding time. The temporal characteristics of this model are analyzed via the autocovariance function, where the effect of event density and mean holding time are shown.
OriginalsprogEngelsk
Titel2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)
Antal sider6
ForlagIEEE
Publikationsdato2018
ISBN (Trykt)978-1-5386-3529-2
ISBN (Elektronisk)978-1-5386-3531-5
DOI
StatusUdgivet - 2018
BegivenhedPIMRC 2017 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications - Montreal, Canada
Varighed: 8 okt. 201713 okt. 2017
http://pimrc2017.ieee-pimrc.org/

Konference

KonferencePIMRC 2017 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications
LandCanada
ByMontreal
Periode08/10/201713/10/2017
Internetadresse
NavnIEEE International Symposium on Personal, Indoor, and Mobile Radio Communications workshops
ISSN2166-9570

Fingerprint

Communication
Base stations
Markov processes
Machine-to-machine communication

Citer dette

Thomsen, H., Manchón, C. N., & Fleury, B. H. (2018). A Traffic Model for Machine-Type Communications Using Spatial Point Processes. I 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) IEEE. IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications workshops https://doi.org/10.1109/PIMRC.2017.8292670
Thomsen, Henning ; Manchón, Carles Navarro ; Fleury, Bernard Henri. / A Traffic Model for Machine-Type Communications Using Spatial Point Processes. 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, 2018. (IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications workshops).
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title = "A Traffic Model for Machine-Type Communications Using Spatial Point Processes",
abstract = "A source traffic model for machine-to-machine communications is presented in this paper. We consider a model in which devices operate in a regular mode until they are triggered into an alarm mode by an alarm event. The positions of devices and events are modeled by means of Poisson point processes, where the generated traffic by a given device depends on its position and event positions. We first consider the case where devices and events are static and devices generate traffic according to a Bernoulli process, where we derive the total rate from the devices at the base station. We then extend the model by defining a two-state Markov chain for each device, which allows for devices to stay in alarm mode for a geometrically distributed holding time. The temporal characteristics of this model are analyzed via the autocovariance function, where the effect of event density and mean holding time are shown.",
keywords = "Machine-type communications, Internet-of-things, Spatial traffic model, Poisson point process",
author = "Henning Thomsen and Manch{\'o}n, {Carles Navarro} and Fleury, {Bernard Henri}",
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Thomsen, H, Manchón, CN & Fleury, BH 2018, A Traffic Model for Machine-Type Communications Using Spatial Point Processes. i 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications workshops, Montreal, Canada, 08/10/2017. https://doi.org/10.1109/PIMRC.2017.8292670

A Traffic Model for Machine-Type Communications Using Spatial Point Processes. / Thomsen, Henning; Manchón, Carles Navarro; Fleury, Bernard Henri.

2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, 2018. (IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications workshops).

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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AU - Manchón, Carles Navarro

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N2 - A source traffic model for machine-to-machine communications is presented in this paper. We consider a model in which devices operate in a regular mode until they are triggered into an alarm mode by an alarm event. The positions of devices and events are modeled by means of Poisson point processes, where the generated traffic by a given device depends on its position and event positions. We first consider the case where devices and events are static and devices generate traffic according to a Bernoulli process, where we derive the total rate from the devices at the base station. We then extend the model by defining a two-state Markov chain for each device, which allows for devices to stay in alarm mode for a geometrically distributed holding time. The temporal characteristics of this model are analyzed via the autocovariance function, where the effect of event density and mean holding time are shown.

AB - A source traffic model for machine-to-machine communications is presented in this paper. We consider a model in which devices operate in a regular mode until they are triggered into an alarm mode by an alarm event. The positions of devices and events are modeled by means of Poisson point processes, where the generated traffic by a given device depends on its position and event positions. We first consider the case where devices and events are static and devices generate traffic according to a Bernoulli process, where we derive the total rate from the devices at the base station. We then extend the model by defining a two-state Markov chain for each device, which allows for devices to stay in alarm mode for a geometrically distributed holding time. The temporal characteristics of this model are analyzed via the autocovariance function, where the effect of event density and mean holding time are shown.

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Thomsen H, Manchón CN, Fleury BH. A Traffic Model for Machine-Type Communications Using Spatial Point Processes. I 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE. 2018. (IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications workshops). https://doi.org/10.1109/PIMRC.2017.8292670