Advancing reliability and efficiency of urban communication: Unmanned aerial vehicles, intelligent reflection surfaces, and deep learning techniques

Li, Chongyang; Qiang, Xiaohu

doi:10.1016/j.heliyon.2024.e32472

Heliyon

2024

DOI: 10.1016/j.heliyon.2024.e32472

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Advancing reliability and efficiency of urban communication: Unmanned aerial vehicles, intelligent reflection surfaces, and deep learning techniques

Chongyang Li,

Xiaohu Qiang

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2024

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Research on Channel Modeling of UAV Based on Artificial Intelligence Reflective Surface

2024

Applied Mathematics and Nonlinear Sciences

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Artificial Intelligent Reflective Surface (AIRS) is a kind of artificial two-dimensional surface with special electromagnetic properties that can control the absorption, reflection, and refraction characteristics of electromagnetic waves, thus realizing the modulation of the channel. It has a broad application prospect. Based on the fading characteristics of wireless channels, the article explores artificial intelligent, reflective surface-related technology and establishes an IRS-assisted UAV-MIMO channel model in combination with the wireless communication link of the UAV. For the statistical characteristics of the UAV channel, wireless in-site simulation software is used to carry out simulation analysis of its impulse response, space-time frequency correlation function, path fading, Doppler power spectral density, and other statistical characteristics. The peak value of the UAV path loss decreases from 143.8 dB to 129.9 dB when the wind speed increases from 6 m/s to 18 m/s in a fixed-height ground environment, and the communication delay distributions are between [0,450 ns] and [0,1550 ns] when the hovering height of the UAV is 100 m and 500 m, respectively. The Rice factor’s Doppler power spectral density value decreases by 53.48% when it is reduced from 1.2 dB to 0.05 dB. The absolute envelope amplitude of the channel of the UAV fluctuates between [-26.3 dB and 21.8 dB] after the optimal reflective phase design based on IRS adaptation. The use of AI reflective surfaces can facilitate the construction of the UAV channel model, thereby improving the communication quality of the UAV channel.

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Research on Channel Modeling of UAV Based on Artificial Intelligence Reflective Surface

2024

Applied Mathematics and Nonlinear Sciences

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Advancing reliability and efficiency of urban communication: Unmanned aerial vehicles, intelligent reflection surfaces, and deep learning techniques

Cited by 1 publication

References 30 publications

Research on Channel Modeling of UAV Based on Artificial Intelligence Reflective Surface

Research on Channel Modeling of UAV Based on Artificial Intelligence Reflective Surface

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