A 3D Non-Stationary MIMO Channel Model for Reconfigurable Intelligent Surface Auxiliary UAV-To-Ground MmWave Communications
Unmanned aerial vehicle (UAV) communications exploiting millimeter wave (mmWave) can satisfy the increasing data rate demands for future wireless networks owing to the line-of-sight (LoS) dominated transmission and flexibility. In reality, the LoS link can be easily and severely blocked due to poor propagation environments such as tall buildings or trees. To this end, we introduce a reconfigurable intelligent surface (RIS), which passively reflects signals with programmable reflection coefficients, between the transceivers to enhance the communication quality. Specifically, in this paper we generalize a three-dimensional (3D) non-stationary wideband end-to-end channel model for RIS auxiliary UAV-to-ground mmWave multiple-input multiple-output (MIMO) communication systems. By modeling the RIS as a virtual cluster, we study the power delivering capability of RIS as well as the fading characteristic of the proposed channel model. Important channel statistical properties are derived and thoroughly investigated, and the impact of RIS reflection phase configurations on these statistical properties is studied, which provides guidelines for the practical system design. The agreement between theoretical and simulated as well as measurement results validate the effectiveness of the proposed channel model.
B. Xiong et al., "A 3D Non-Stationary MIMO Channel Model for Reconfigurable Intelligent Surface Auxiliary UAV-To-Ground MmWave Communications," IEEE Transactions on Wireless Communications, vol. 21, no. 7, pp. 5658 - 5672, Institute of Electrical and Electronics Engineers, Jul 2022.
The definitive version is available at https://doi.org/10.1109/TWC.2022.3142437
Electrical and Computer Engineering
Keywords and Phrases
non-stationary UAV-to-ground mmWave channel model; power delivering capability; Reconfigurable intelligent surface; reflection phase; statistical properties
International Standard Serial Number (ISSN)
Article - Journal
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01 Jul 2022