A Cluster-Based Dynamic Narrow-Beam Channel Model for Vehicle-to-Infrastructure Communications

Vehicle-to-infrastructure (V2I) communications have attracted much attention in recent years due to its application in intelligent transportation systems. To apply the dynamic beamforming technology in V2I communications, an accurate V2I narrow-beam channel model is required. This paper investigates cluster-based dynamic narrow-beam channel modeling for V2I scenarios. Firstly, a phased-array antenna based channel measurement system is designed and used to perform a series of narrow-beam channel measurements at 3.35 GHz in V2I highway scenarios. Data processing methods such as beam synthesis, angle estimation based on single-scattering assumption, and variational Bayesian Gaussian mixture model clustering are applied to extract parameters of multipath components and clusters. Then, we propose a cluster-based dynamic narrow-beam channel model, which considers the directional attenuation of narrow-beam and non-stationarity of clusters. In this model, the parameters of spatial-temporal characteristics are divided into global-cluster parameters and scatterer-cluster parameters, and the statistical distribution of these parameters are studied and modeled. Finally, a simulation method for the proposed channel model is provided, and model validation results show a good match between measurements and simulations in terms of channel characteristics such as delay spread and angle spread. This model provides a better characterization of the V2I narrow-beam channel and will be useful for designing and evaluating V2I communication systems.

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Publication Details

Journal
IEEE Transactions on Wireless Communications
Published
2024-08-05
DOI
https://doi.org/10.1109/twc.2024.3434677
Citations
4
Primary Topic
Millimeter-Wave Propagation and Modeling
Type
article
Field-Weighted Citation Impact
0.83

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article

A Cluster-Based Dynamic Narrow-Beam Channel Model for Vehicle-to-Infrastructure Communications

Liu Liu, Yiqun Liang, Tianyun Feng, Tao Zhou et al.
4 citations
IEEE Transactions on Wireless Communications
Millimeter-Wave Propagation and Modeling
0.83
article

A Cluster-Based Dynamic Narrow-Beam Channel Model for Vehicle-to-Infrastructure Communications

Liu Liu, Yiqun Liang, Tianyun Feng, Tao Zhou, Bo Ai, Wenliang Zhang
article en
4 citations

Abstract

Vehicle-to-infrastructure (V2I) communications have attracted much attention in recent years due to its application in intelligent transportation systems. To apply the dynamic beamforming technology in V2I communications, an accurate V2I narrow-beam channel model is required. This paper investigates cluster-based dynamic narrow-beam channel modeling for V2I scenarios. Firstly, a phased-array antenna based channel measurement system is designed and used to perform a series of narrow-beam channel measurements at 3.35 GHz in V2I highway scenarios. Data processing methods such as beam synthesis, angle estimation based on single-scattering assumption, and variational Bayesian Gaussian mixture model clustering are applied to extract parameters of multipath components and clusters. Then, we propose a cluster-based dynamic narrow-beam channel model, which considers the directional attenuation of narrow-beam and non-stationarity of clusters. In this model, the parameters of spatial-temporal characteristics are divided into global-cluster parameters and scatterer-cluster parameters, and the statistical distribution of these parameters are studied and modeled. Finally, a simulation method for the proposed channel model is provided, and model validation results show a good match between measurements and simulations in terms of channel characteristics such as delay spread and angle spread. This model provides a better characterization of the V2I narrow-beam channel and will be useful for designing and evaluating V2I communication systems.

IEEE Transactions on Wireless CommunicationsVol. 23(11)
Beijing Jiaotong University (CN), China Academy of Railway Sciences (CN)
National Natural Science Foundation of China, National University of Science and Technology
Industry, innovation and infrastructure
Openalex Percentile: Top 27%
Millimeter-Wave Propagation and Modeling
0.83
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