Effects of sampling frequency on node mobility prediction in dynamic networks: A spectral view

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10253497" target="_blank" >RIV/61989100:27240/23:10253497 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/23:10253497

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S2352864822000992" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2352864822000992</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.dcan.2022.05.008" target="_blank" >10.1016/j.dcan.2022.05.008</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Effects of sampling frequency on node mobility prediction in dynamic networks: A spectral view

Popis výsledku v původním jazyce

The field of mobility prediction has been widely investigated in the recent past, especially the reduction of the coverage radius of cellular networks, which led to an increase in hand-over events. Changing the cell coverage very frequently, for example, may lead to service disruptions if a predictive approach is not deployed in the system. Although several works examined mobility prediction in the new-generation mobile networks, all of these studies focused on studying the time features of mobility traces, and the spectral content of historical mobility patterns was not considered for prediction purposes as yet. In the present study, we propose a new approach to mobility prediction by analyzing the effects of a proper mobility sampling frequency. The proposed approach lies in the mobility analysis in the frequency domain, to extract hidden features of the mobility process. Thus, we proposed a new methodology to determine the spectral content of mobility traces (considered as signals) and, thus, the appropriate sampling frequency, which can provide numerous advantages. We considered several types of mobility models (e.g. pedestrian, urban, and vehicular), containing important details in the time and frequency domains. Several simulation campaigns were performed to observe and analyze the characteristics of mobility from real traces and to evaluate the effects of sampling frequency on the spectral content. (C) 2022 Chongqing University of Posts and Telecommunications

Název v anglickém jazyce

Effects of sampling frequency on node mobility prediction in dynamic networks: A spectral view

Popis výsledku anglicky

The field of mobility prediction has been widely investigated in the recent past, especially the reduction of the coverage radius of cellular networks, which led to an increase in hand-over events. Changing the cell coverage very frequently, for example, may lead to service disruptions if a predictive approach is not deployed in the system. Although several works examined mobility prediction in the new-generation mobile networks, all of these studies focused on studying the time features of mobility traces, and the spectral content of historical mobility patterns was not considered for prediction purposes as yet. In the present study, we propose a new approach to mobility prediction by analyzing the effects of a proper mobility sampling frequency. The proposed approach lies in the mobility analysis in the frequency domain, to extract hidden features of the mobility process. Thus, we proposed a new methodology to determine the spectral content of mobility traces (considered as signals) and, thus, the appropriate sampling frequency, which can provide numerous advantages. We considered several types of mobility models (e.g. pedestrian, urban, and vehicular), containing important details in the time and frequency domains. Several simulation campaigns were performed to observe and analyze the characteristics of mobility from real traces and to evaluate the effects of sampling frequency on the spectral content. (C) 2022 Chongqing University of Posts and Telecommunications

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20203 - Telecommunications

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Digital Communications and Networks

ISSN

2468-5925

e-ISSN

—

Svazek periodika

9

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CN - Čínská lidová republika

Počet stran výsledku

14

Strana od-do

1009-1022

Kód UT WoS článku

001075113800001

EID výsledku v databázi Scopus

2-s2.0-85165207896