Time-Dependent Propagation Analysis and Modeling of LPWAN Technologies

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU137835" target="_blank" >RIV/00216305:26220/20:PU137835 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9367525" target="_blank" >https://ieeexplore.ieee.org/document/9367525</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/GCWkshps50303.2020.9367525" target="_blank" >10.1109/GCWkshps50303.2020.9367525</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Time-Dependent Propagation Analysis and Modeling of LPWAN Technologies

Popis výsledku v původním jazyce

The modern low-power wide area network (LPWAN) technologies have been introduced as connectivity enablers with low complexity, extended communication range, and excellent signal penetration. On the other hand, they suffer from a substantial delay and low packet-delivery guarantees. As a result, numerous novel applications entering the market suffer from insufficient performance. To mitigate this, further optimization and adaptation of the LPWAN technologies to the needs of these new applications requires an in-depth understanding of the propagation environment dynamics. Motivated by that, in this paper, we thoroughly investigate time-dependent statistical characteristics of the reference signal receive power (RSRP) dynamics of Narrowband IoT (NB-IoT) technology. We demonstrate that even for a stationary user equipment (UE), RSRP is subject to drastic variations that are characterized by exponentially decaying autocorrelation function (ACF). We then demonstrate that first- and second-order statistical properties of the RSRP dynamics can be closely captured using the doubly-stochastic Markov model that retains the tractability of the conventional Markov models. The reported models are expected to serve as a building block for analytical and simulation-based system-level studies and optimization of LPWAN technologies.

Název v anglickém jazyce

Time-Dependent Propagation Analysis and Modeling of LPWAN Technologies

Popis výsledku anglicky

The modern low-power wide area network (LPWAN) technologies have been introduced as connectivity enablers with low complexity, extended communication range, and excellent signal penetration. On the other hand, they suffer from a substantial delay and low packet-delivery guarantees. As a result, numerous novel applications entering the market suffer from insufficient performance. To mitigate this, further optimization and adaptation of the LPWAN technologies to the needs of these new applications requires an in-depth understanding of the propagation environment dynamics. Motivated by that, in this paper, we thoroughly investigate time-dependent statistical characteristics of the reference signal receive power (RSRP) dynamics of Narrowband IoT (NB-IoT) technology. We demonstrate that even for a stationary user equipment (UE), RSRP is subject to drastic variations that are characterized by exponentially decaying autocorrelation function (ACF). We then demonstrate that first- and second-order statistical properties of the RSRP dynamics can be closely captured using the doubly-stochastic Markov model that retains the tractability of the conventional Markov models. The reported models are expected to serve as a building block for analytical and simulation-based system-level studies and optimization of LPWAN technologies.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20203 - Telecommunications

Projekt

<a href="/cs/project/FV40371" target="_blank" >FV40371: Pokročilý systém pro vnitřní 2D a 3D lokalizaci v reálném čase pro automatizaci, vizualizaci a řízení výrobních procesů v Průmyslu 4.0 – řešení na bázi MEMS a PDoA/AoA hybridních metod</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2020 IEEE Global Communications Conference

ISBN

978-1-7281-7307-8

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

1-6

Název nakladatele

Neuveden

Místo vydání

neuveden

Místo konání akce

Taipei

Datum konání akce

7. 12. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000662202100129