An enhanced approach to virtually increase quasi-stationarity regions within geometric channel models for vehicular communications
Fecha
2023Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión aceptada / Onetsi den bertsioa
Identificador del proyecto
//PID2021-127409OB-C31
Impacto
|
10.1109/LAWP.2023.3281081
Resumen
Vehicular communication channels are intrinsically
non-stationary, as they present high mobility and abundant dynamic
scatterers. Quasi-stationary regions can assess the degree
of non-stationarity within a determined scenario and time variant
observation of the channel can be extracted. These regions can
aid geometrical models as to increase channel sampling intervals
or to develop hybrid s ...
[++]
Vehicular communication channels are intrinsically
non-stationary, as they present high mobility and abundant dynamic
scatterers. Quasi-stationary regions can assess the degree
of non-stationarity within a determined scenario and time variant
observation of the channel can be extracted. These regions can
aid geometrical models as to increase channel sampling intervals
or to develop hybrid stochastic-geometric channel models. In this
work, a new methodology for the use of virtual quasi-stationary
regions within geometric channel models is proposed, in order to
leverage the inherent location information to virtually increase
their size. Overall, the use of delay-shifted channel responses
improves the mean correlation coefficient between consecutive
locations, ultimately reducing computation time for time-variant
geometric channel models. [--]
Materias
Non-stationarity,
3D ray-launching,
Correlation matrix,
Quasi-stationarity regions,
Geometric channel models,
V2X
Editor
IEEE
Publicado en
IEEE Antennas and Wireless Propagation Letters 22(9), 2180-20184
Departamento
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila /
Universidad Pública de Navarra. Departamento de Ingeniería Eléctrica, Electrónica y de Comunicación /
Nafarroako Unibertsitate Publikoa. Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza Saila /
Universidad Pública de Navarra/Nafarroako Unibertsitate Publikoa. Institute of Smart Cities - ISC
Versión del editor
Entidades Financiadoras
The authors wish to acknowledge the support received under Grant RYC2021-031949-I, funded by
MCIN/AEI/10.13039/501100011033 and NextGenerationEU/PRTR; and under
Grant PID2021-127409OB-C31, funded by MCIU/AEI/FEDER, UE.