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

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

2021IEEE Wireless Communications Letters16 citationsDOI

Abstract

Any operation scenario for unmanned aerial vehicles also known as drones in real world requires resilient wireless link to guarantee capacity and performance for users, which can only be achieved by obtaining detailed knowledge about the propagation channel. Thus, this study investigates the large-scale channel propagation statistics for the line of sight air–to–air (A2A) drone communications to estimate the path loss exponent (PLE). We conducted a measurement campaign at 5.8 GHz, using low cost and light weight software defined radio based channel sounder which is developed in this study and then further integrated on commercially available drones. To determine the PLE, frequency-based, time-based and time–frequency based methods are utilized. Accuracy of the proposed method is verified under ideal conditions in a well-isolated anechoic chamber before the actual measurement campaign to verify the performance in a free space path loss environment. The path loss exponent for A2A wireless drone channel is estimated with these verified methods.

Topics & Concepts

DronePath lossComputer scienceWirelessChannel (broadcasting)Anechoic chamberReal-time computingElectronic engineeringSimulationTelecommunicationsEngineeringGeneticsBiologyUAV Applications and OptimizationMillimeter-Wave Propagation and ModelingVehicular Ad Hoc Networks (VANETs)
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