A physical air-to-ground modeling method with dynamic investigations for integrated sensing and communication

Integrated sensing and communication (ISAC) is one of the key technologies in the sixth-generation (6G) wireless communication network. Unmanned aerial vehicles (UAVs) are essential for their flexible deployment, wide coverage, and high mobility. However, these attributes pose challenges for channel research. This paper presents a novel physical communication model for 6G ISAC in multiple-input multiple-output (MIMO) air-to-ground wireless channels. Here, the direct propagation link between the UAV transmitter and vehicle receiver is obstructed by buildings, hindering successful signal transmission. To address this, we propose employing double intelligent reflecting surfaces (IRSs) to assist signal transmission, forming the propagation links with either double or single IRSs along with the non-line-of-sight (NLoS) path. We investigate the complex channel impulse responses (CIRs) of these links considering multipath effects and derive the complete channel matrix. Additionally, we analyze the statistical properties of the communication model across various parameters. Leveraging these derivations, we illustrate the propagation characteristics of the MIMO UAV-to-vehicle communication model empowered by double IRSs. Simulation results highlight the superior channel characteristics of double- IRSs compared to single-IRSs, underscoring the significance of integrating double IRSs into the UAV-to-vehicle channel model.

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Publication Details

Journal
Journal of Communications and Networks
Published
2024-10-01
DOI
https://doi.org/10.23919/jcn.2024.000041
Primary Topic
Radio Wave Propagation Studies
Type
article
Field-Weighted Citation Impact
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article

A physical air-to-ground modeling method with dynamic investigations for integrated sensing and communication

Honglin Wang, Cheng Zhu, Dasong Sun, Caiyun Sun
Journal of Communications and Networks
Radio Wave Propagation Studies
article

A physical air-to-ground modeling method with dynamic investigations for integrated sensing and communication

Honglin Wang, Cheng Zhu, Dasong Sun, Caiyun Sun
article en

Abstract

Integrated sensing and communication (ISAC) is one of the key technologies in the sixth-generation (6G) wireless communication network. Unmanned aerial vehicles (UAVs) are essential for their flexible deployment, wide coverage, and high mobility. However, these attributes pose challenges for channel research. This paper presents a novel physical communication model for 6G ISAC in multiple-input multiple-output (MIMO) air-to-ground wireless channels. Here, the direct propagation link between the UAV transmitter and vehicle receiver is obstructed by buildings, hindering successful signal transmission. To address this, we propose employing double intelligent reflecting surfaces (IRSs) to assist signal transmission, forming the propagation links with either double or single IRSs along with the non-line-of-sight (NLoS) path. We investigate the complex channel impulse responses (CIRs) of these links considering multipath effects and derive the complete channel matrix. Additionally, we analyze the statistical properties of the communication model across various parameters. Leveraging these derivations, we illustrate the propagation characteristics of the MIMO UAV-to-vehicle communication model empowered by double IRSs. Simulation results highlight the superior channel characteristics of double- IRSs compared to single-IRSs, underscoring the significance of integrating double IRSs into the UAV-to-vehicle channel model.

Journal of Communications and NetworksVol. 26(5)
Nanjing University of Finance and Economics (CN), University of Illinois Urbana-Champaign (US), Nanjing University of Information Science and Technology (CN)
Openalex Percentile: Top 69%
Radio Wave Propagation Studies
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A physical air-to-ground modeling method with dynamic investigations for integrated sensing and communication — Honglin Wang, Cheng Zhu, et al. · Journal of Communications and Networks (2024) | TGRS Research Map | TGRS