Multiple-Frequency-Bands Channel Characterization for In-vehicle Wireless Networks
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866914963524681728 |
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| author | Li, Mengting Li, Yifa Zeng, Qiyu Olesen, Kim Zhang, Fengchun Fan, Wei |
| author_facet | Li, Mengting Li, Yifa Zeng, Qiyu Olesen, Kim Zhang, Fengchun Fan, Wei |
| contents | In-vehicle wireless networks are crucial for advancing smart transportation systems and enhancing interaction among vehicles and their occupants. However, there are limited studies in the current state of the art that investigate the in-vehicle channel characteristics in multiple frequency bands. In this paper, we present measurement campaigns conducted in a van and a car across below 7 GHz, millimeter-wave (mmWave), and sub-Terahertz (Sub-THz) bands. These campaigns aim to compare the channel characteristics for in-vehicle scenarios across various frequency bands. Channel impulse responses (CIRs) were measured at various locations distributed across the engine compartment of both the van and car. The CIR results reveal a high similarity in the delay properties between frequency bands below 7GHz and mmWave bands for the measurements in the engine bay. Sparse channels can be observed at Sub-THz bands in the engine bay scenarios. Channel spatial profiles in the passenger cabin of both the van and car are obtained by the directional scan sounding scheme for three bands. We compare the power angle delay profiles (PADPs) measured at different frequency bands in two line of sight (LOS) scenarios and one non-LOS (NLOS) scenario. Some major \added{multipath components (MPCs)} can be identified in all frequency bands and their trajectories are traced based on the geometry of the vehicles. The angular spread of arrival is also calculated for three scenarios. The analysis of channel characteristics in this paper can enhance our understanding of in-vehicle channels and foster the evolution of in-vehicle wireless networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_02410 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Multiple-Frequency-Bands Channel Characterization for In-vehicle Wireless Networks Li, Mengting Li, Yifa Zeng, Qiyu Olesen, Kim Zhang, Fengchun Fan, Wei Signal Processing In-vehicle wireless networks are crucial for advancing smart transportation systems and enhancing interaction among vehicles and their occupants. However, there are limited studies in the current state of the art that investigate the in-vehicle channel characteristics in multiple frequency bands. In this paper, we present measurement campaigns conducted in a van and a car across below 7 GHz, millimeter-wave (mmWave), and sub-Terahertz (Sub-THz) bands. These campaigns aim to compare the channel characteristics for in-vehicle scenarios across various frequency bands. Channel impulse responses (CIRs) were measured at various locations distributed across the engine compartment of both the van and car. The CIR results reveal a high similarity in the delay properties between frequency bands below 7GHz and mmWave bands for the measurements in the engine bay. Sparse channels can be observed at Sub-THz bands in the engine bay scenarios. Channel spatial profiles in the passenger cabin of both the van and car are obtained by the directional scan sounding scheme for three bands. We compare the power angle delay profiles (PADPs) measured at different frequency bands in two line of sight (LOS) scenarios and one non-LOS (NLOS) scenario. Some major \added{multipath components (MPCs)} can be identified in all frequency bands and their trajectories are traced based on the geometry of the vehicles. The angular spread of arrival is also calculated for three scenarios. The analysis of channel characteristics in this paper can enhance our understanding of in-vehicle channels and foster the evolution of in-vehicle wireless networks. |
| title | Multiple-Frequency-Bands Channel Characterization for In-vehicle Wireless Networks |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2410.02410 |