The Journal of China Universities of Posts and Telecommunications

The Journal of China Universities of Posts and Telecommunications ›› 2023, Vol. 30 ›› Issue (6): 60-67.doi: 10.19682/j.cnki.1005-8885.2023.1012

Special Issue: 复杂网络传播与网络控制

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Characteristics and modeling of UAV-vehicle MIMO wideband channels

Liang Xiaolin, Ma Jiaxu, Cao Wangbin, Xu Jianpeng, Liu Shuaiqi, Zhao Xiongwen   

  1. 1. College of Electronic and Information Engineering, Hebei University, Baoding 071002, China
    2. Hebei Key Laboratory of Power Internet of Things Technology, North China Electric Power University, Baoding 071003, China
    3. School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China
    4. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
  • Received:2023-06-07 Revised:2023-10-03 Online:2023-12-28 Published:2023-12-28
  • Contact: Ma Jiaxu E-mail:mjx.hbu@foxmail.com
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (62001166, 62172139), and the Natural
    Science Foundation of Hebei Province of China (F2022201055).

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Abstract: A geometry-based stochastic model ( GBSM) for unmanned aerial vehicle to vehicle ( UAV-V) multiple-input multiple-output (MIMO) wideband channel is proposed to investigate the characteristics of UAV-V channel. Based on the proposed model, a three-dimensional (3D) wideband channel matrix regarding channel numbers, time and delay is constructed. And some important channel characteristics parameters, such as power delay profile (PDP), root mean square ( RMS) delay spread, RMS Doppler spread, channel gain and Doppler power spectral density (PSD) are investigated with different vehicle velocities. It is much simpler and clearer compared with the complex analytical derivations. The results are compared with validated analysis to confirm the theoretical analysis.

Key words: unmanned aerial vehicle to vehicle (UAV-V), wideband channel, geometry-based stochastic model (GBSM), channel characteristics

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