Relative Position-Aware Channel Modeling for UAV-Assisted Low-Power Wireless Networks

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Abstract
Accurate and reliable channel modeling is crucial for uncrewed aerial vehicles (UAVs)-assisted low-power wireless networks. However, existing research has shown that existing channel models are not accurate in this scenario. This article evaluates existing channel models and analyzes the factors impacting the accuracy of channel modeling. The results show that the path loss exponent (PLE) and antenna irregularity will affect the path loss under different flight modes. Based on the above finding, by considering the PLE and antenna irregularity, this article proposes a channel modeling method based on the relative position of the UAV and ground node. The experimental results show that the proposed model is suitable for UAV-assisted low-power wireless networks. The proposed method greatly reduces the estimation error of path loss under the premise of low computation overhead. Compared with existing channel models, thanks to more comprehensive considerations of the proposed method, the estimation error of the model established by the proposed method is reduced by 4.42%–92.78% under the ground-to-air (GA) channel and 13.23%–82.12% under the air-to-ground (AG) channel.
Funding Information
  • Scientific Research Foundation of Chongqing University of Technology
  • Industry-university-research Innovation Fund for Chinese Universities (2021ZYA04004)
  • Scientific and Technological Research Program of Chongqing Municipal Education Commission (2021ZYA04004, KJQN202001110)

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