Large-Scale RIS Enabled Air-Ground Channels: Near-Field Modeling and Analysis

• Published in: arXiv.org 2024-03
• Main Authors: Jiang, Hao, Shi, Wangqi, Zhang, Zaichen, Pan, Cunhua, Wu, Qingqing, Feng, Shu, Liu, Ruiqi, Wang, Jiangzhou
• Format: Article
• Language: English
• Subjects: Accuracy; Arrays; Autocorrelation functions; Channels; Complexity; Cross correlation; Far fields; Model accuracy; Modelling; Near fields; Wireless communication systems; Wireless networks
• ISSN: 2331-8422

Existing works mainly rely on the far-field planar-wave-based channel model to assess the performance of reconfigurable intelligent surface (RIS)-enabled wireless communication systems. However, when the transmitter and receiver are in near-field ranges, this will result in relatively low computing accuracy. To tackle this challenge, we initially develop an analytical framework for sub-array partitioning. This framework divides the large-scale RIS array into multiple sub-arrays, effectively reducing modeling complexity while maintaining acceptable accuracy. Then, we develop a beam domain channel model based on the proposed sub-array partition framework for large-scale RIS-enabled UAV-to-vehicle communication systems, which can be used to efficiently capture the sparse features in RIS-enabled UAV-to-vehicle channels in both near-field and far-field ranges. Furthermore, some important propagation characteristics of the proposed channel model, including the spatial cross-correlation functions (CCFs), temporal auto-correlation functions (ACFs), frequency correlation functions (CFs), and channel capacities with respect to the different physical features of the RIS and non-stationary properties of the channel model are derived and analyzed. Finally, simulation results are provided to demonstrate that the proposed framework is helpful to achieve a good tradeoff between model complexity and accuracy for investigating the channel propagation characteristics, and therefore providing highly-efficient communications in RIS-enabled UAV-to-vehicle wireless networks.