A Novel Site-Specific Inference Model for Urban Canyon Channels: From Measurements to Modeling

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Song, Junzhe, He, Ruisi, Yang, Mi, Zhang, Zhengyu, Chen, Xinwen, Zhang, Xiaoying, Ai, Bo
Formato: Preprint
Publicado: 2025
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866918453836775424
author Song, Junzhe
He, Ruisi
Yang, Mi
Zhang, Zhengyu
Chen, Xinwen
Zhang, Xiaoying
Ai, Bo
author_facet Song, Junzhe
He, Ruisi
Yang, Mi
Zhang, Zhengyu
Chen, Xinwen
Zhang, Xiaoying
Ai, Bo
contents With the rapid development of intelligent transportation and smart city applications, urban canyon has become a critical scenario for the design and evaluation of wireless communication systems. Due to its unique environmental layout, the channel characteristics in urban canyon are strongly a street geometry and building distribution, thereby exhibiting significant site-specific channel condition. However, this feature has not been well captured in existing channel models. In this paper, we propose a site-specific channel inference model based on environmental geometry, the model is parameterized using sub-6GHz channel measurements. Multipath components (MPCs) are extracted and clustered according to geometric propagation, which are explicitly derived from the influence of canyon width, thereby establishing an interpretable mapping between the physical environment and statistical characteristics of MPCs. A step-by-step implementation scheme is presented. Subsequently, the proposed site-specific channel inference model is validated by comparing second-order statistics of channels, derived from the model and measurements. The results show that the proposed model achieves high accuracy and robustness in different urban canyon scenarios.
format Preprint
id arxiv_https___arxiv_org_abs_2509_19275
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Novel Site-Specific Inference Model for Urban Canyon Channels: From Measurements to Modeling
Song, Junzhe
He, Ruisi
Yang, Mi
Zhang, Zhengyu
Chen, Xinwen
Zhang, Xiaoying
Ai, Bo
Signal Processing
With the rapid development of intelligent transportation and smart city applications, urban canyon has become a critical scenario for the design and evaluation of wireless communication systems. Due to its unique environmental layout, the channel characteristics in urban canyon are strongly a street geometry and building distribution, thereby exhibiting significant site-specific channel condition. However, this feature has not been well captured in existing channel models. In this paper, we propose a site-specific channel inference model based on environmental geometry, the model is parameterized using sub-6GHz channel measurements. Multipath components (MPCs) are extracted and clustered according to geometric propagation, which are explicitly derived from the influence of canyon width, thereby establishing an interpretable mapping between the physical environment and statistical characteristics of MPCs. A step-by-step implementation scheme is presented. Subsequently, the proposed site-specific channel inference model is validated by comparing second-order statistics of channels, derived from the model and measurements. The results show that the proposed model achieves high accuracy and robustness in different urban canyon scenarios.
title A Novel Site-Specific Inference Model for Urban Canyon Channels: From Measurements to Modeling
topic Signal Processing
url https://arxiv.org/abs/2509.19275