Measurement-Based Large Scale Statistical Modeling of Air–to–Air Wireless UAV Channels via Novel Time–Frequency Analysis

Ede, Burak; Kaplan, Batuhan; Kahraman, Ibrahim; Keşir, Samed; Yarkan, Serhan; Ekti, Ali Rıza; Baykaş, Tunçer; Görçin, Ali; Çırpan, Hakan Ali

doi:10.1109/lwc.2021.3122281

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…Furthermore, they introduced a modified log-distance path-loss model. Similar investigations were undertaken by Ede et al and Zhou et al, who estimated path-loss exponents and proposed path-loss models for A2A communications based on measurement and ray-tracing results [17,18]. In general, A2A channel modeling on small-scale fading is still in its early stages, with most studies relying on classical geometric models such as the ellipsoid model [19], two-sphere model [20], and cylinder model [21].…”

Section: Related Workmentioning

confidence: 67%

A Novel UAV Air-to-Air Channel Model Incorporating the Effect of UAV Vibrations and Diffuse Scattering

Qi,

Bian,

Wang

et al. 2024

Drones

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In this paper, we propose a geometric channel model for air-to-air (A2A) unmanned aerial vehicle (UAV) communication scenarios. The model is established by incorporating line-of-sight, specular reflection, and diffuse scattering components, and it can capture the impacts of UAV vibrations induced by the propeller’s rotation. Based on UAV heights and ground scatterer density, a closed-form expression is derived to jointly capture the zenith and azimuth angular distributions of diffuse rays. The power of diffuse rays is modeled according to the grazing angle of the rays and the electrical properties and roughness of the ground materials. Key statistics, including the temporal autocorrelation function, spatial cross-correlation function, Doppler power spectrum density, and coherence time are derived, providing an in-depth understanding of the time-variant characteristics of the channel. The results indicate that the presented model is capable of capturing certain A2A channel characteristics, which align with the corresponding theoretical analysis. The findings suggest that the scattering effect of the A2A channel is significantly influenced by the altitude of the UAV. Additionally, it is shown that UAV vibrations can introduce extra Doppler frequencies, notably decreasing the temporal correlation and coherence time of the channel. This effect is more prominent when the system operates at high-frequency bands. The effectiveness of the presented model is confirmed through a comparison of its statistics with those of an existing model and with available measurement data.

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Section: Related Workmentioning

confidence: 67%

A Novel UAV Air-to-Air Channel Model Incorporating the Effect of UAV Vibrations and Diffuse Scattering

Qi,

Bian,

Wang

et al. 2024

Drones

View full text Add to dashboard Cite

show abstract

“…The work shown by Burak Ede et al [ 17 ] described what the authors defined as: large-scale statistical modelling of air–to–air wireless UAV channels. This statistical modelling was created by using, among other features, propagation characterization of wireless communications enabled by Software Defined Radio (SDR) capabilities.…”

Section: Related Workmentioning

confidence: 99%

An Inexpensive Unmanned Aerial Vehicle-Based Tool for Mobile Network Output Analysis and Visualization

Buggiani

Ortega

Silva

et al. 2023

Sensors

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Usage of Unmanned Aerial Vehicles (UAVs) for different tasks is widespread, as UAVs are affordable, easy to manoeuvre and versatile enough to execute missions in a reliable manner. However, there are still fields where UAVs play a minimal role regardless of their possibilities. One of these application domains is mobile network testing and measurement. Currently, the procedures used to measure the main parameters of mobile networks in an area (such as power output or its distribution in a three-dimensional space) rely on a team of specialized people performing measurements with an array of tools. This procedure is significantly expensive, time consuming and the resulting outputs leave a higher degree of precision to be desired. An open-source UAV-based Cyber-Physical System is put forward that, by means of the Galileo satellite network, a Mobile Data Acquisition System and a Graphical User Interface, can quickly retrieve reliable data from mobile network signals in a three-dimensional space with high accuracy for its visualization and analysis. The UAV tested flew at 40.43 latitude and −3.65 longitude degrees as coordinates, with an altitude over sea level of around 600–800 m through more than 40 mobile network cells and signal power displayed between −75 and −113 decibels.

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“…A large-scale statistical model for an A2A channel was proposed in [ 40 ], in which measurements were carried out at 5.8 GHz, employing two small-sized drones (hexacopters), which carried the equipment. The coupling effect of the antenna mounted on the drones was initially investigated by using an anechoic chamber.…”

Section: Air-to-air Channel Modelsmentioning

confidence: 99%

A Survey of Path Loss Prediction and Channel Models for Unmanned Aerial Systems for System-Level Simulations

Moraitis

Psychogios

Panagopoulos

2023

Sensors

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Unmanned aerial systems (UAS) have recently gained popularity, and they are envisioned as an integral parts of the current and future wireless and mobile-radio networks. Despite the exhaustive research on air-to-ground channels, there are insufficient studies, experimental campaigns and general channel models related to air-to-space (A2S) and air-to-air (A2A) wireless links. This paper presents a comprehensive review of the available channel models and path-loss prediction for A2S and A2A communications. Specific case studies attempting to extend current models’ parameters and provide important knowledge of the channel behavior in combination with UAV flight characteristics are also provided. A time-series rain-attenuation synthesizer is also presented that describes quite accurately the impact of the troposphere at frequencies above 10 GHz. This specific model can be also applied to both A2S and A2A wireless links. Finally, scientific challenges and gaps that can be used for future research on the upcoming 6G networks are highlighted.

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Measurement-Based Large Scale Statistical Modeling of Air–to–Air Wireless UAV Channels via Novel Time–Frequency Analysis

Cited by 7 publications

References 10 publications

A Novel UAV Air-to-Air Channel Model Incorporating the Effect of UAV Vibrations and Diffuse Scattering

A Novel UAV Air-to-Air Channel Model Incorporating the Effect of UAV Vibrations and Diffuse Scattering

An Inexpensive Unmanned Aerial Vehicle-Based Tool for Mobile Network Output Analysis and Visualization

A Survey of Path Loss Prediction and Channel Models for Unmanned Aerial Systems for System-Level Simulations

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