Emulating UAV Motion by Utilizing Robotic Arm for mmWave Wireless Channel Characterization
In this article, millimeter-wave (mmWave) wireless channel characteristics (Doppler spread and path loss modeling) for unmanned aerial vehicle (UAV)-assisted communication is analyzed and studied by emulating the real UAV motion using a robotic arm. The motion considers the actual turbulence caused...
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| Veröffentlicht in: | IEEE transactions on antennas and propagation 2021-10, Vol.69 (10), p.6691-6701 |
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| container_title | IEEE transactions on antennas and propagation |
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| creator | Kachroo, Amit Thornton, Collin A. Sarker, Md. Arifur Rahman Choi, Wooyeol Bai, He Song, Ickhyun O'Hara, John F. Ekin, Sabit |
| description | In this article, millimeter-wave (mmWave) wireless channel characteristics (Doppler spread and path loss modeling) for unmanned aerial vehicle (UAV)-assisted communication is analyzed and studied by emulating the real UAV motion using a robotic arm. The motion considers the actual turbulence caused by the wind gusts to the UAV in the atmosphere, which is statistically modeled by the widely used Dryden wind model. The frequency under consideration is 28 GHz in an anechoic chamber setting. A total of 11 distance points from 3.5 to 23.5 ft in increments of 2 ft were considered in this experiment. At each distance point, three samples of data were collected for better inference purposes. In this emulated environment, it was found out that the average Doppler spread at these different distances was around −20 and +20 Hz at the noise floor of −60 dB. On the other hand, the path loss exponent was found to be 1.843. This study presents and lays out a novel framework of emulating UAV motion for mmWave communication systems, which will pave the way out for future design and implementation of next-generation UAV-assisted wireless communication systems. |
| doi_str_mv | 10.1109/TAP.2021.3069484 |
| format | Article |
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Arifur Rahman ; Choi, Wooyeol ; Bai, He ; Song, Ickhyun ; O'Hara, John F. ; Ekin, Sabit</creator><creatorcontrib>Kachroo, Amit ; Thornton, Collin A. ; Sarker, Md. Arifur Rahman ; Choi, Wooyeol ; Bai, He ; Song, Ickhyun ; O'Hara, John F. ; Ekin, Sabit</creatorcontrib><description>In this article, millimeter-wave (mmWave) wireless channel characteristics (Doppler spread and path loss modeling) for unmanned aerial vehicle (UAV)-assisted communication is analyzed and studied by emulating the real UAV motion using a robotic arm. The motion considers the actual turbulence caused by the wind gusts to the UAV in the atmosphere, which is statistically modeled by the widely used Dryden wind model. The frequency under consideration is 28 GHz in an anechoic chamber setting. A total of 11 distance points from 3.5 to 23.5 ft in increments of 2 ft were considered in this experiment. At each distance point, three samples of data were collected for better inference purposes. In this emulated environment, it was found out that the average Doppler spread at these different distances was around −20 and +20 Hz at the noise floor of −60 dB. On the other hand, the path loss exponent was found to be 1.843. 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A total of 11 distance points from 3.5 to 23.5 ft in increments of 2 ft were considered in this experiment. At each distance point, three samples of data were collected for better inference purposes. In this emulated environment, it was found out that the average Doppler spread at these different distances was around −20 and +20 Hz at the noise floor of −60 dB. On the other hand, the path loss exponent was found to be 1.843. This study presents and lays out a novel framework of emulating UAV motion for mmWave communication systems, which will pave the way out for future design and implementation of next-generation UAV-assisted wireless communication systems.</description><subject>Analytical models</subject><subject>Anechoic chambers</subject><subject>Atmospheric modeling</subject><subject>Atmospheric models</subject><subject>Channel emulation</subject><subject>Communication</subject><subject>Doppler</subject><subject>Doppler effect</subject><subject>Dryden wind model</subject><subject>Gusts</subject><subject>Manipulators</subject><subject>Millimeter wave communication</subject><subject>Millimeter waves</subject><subject>millimeter-wave (mmWave)</subject><subject>Noise levels</subject><subject>path loss</subject><subject>Robot arms</subject><subject>Robots</subject><subject>Statistical methods</subject><subject>unmanned aerial vehicle (UAV)</subject><subject>Unmanned aerial vehicles</subject><subject>Wireless communication</subject><subject>Wireless communication systems</subject><issn>0018-926X</issn><issn>1558-2221</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9UFtLwzAYDaLgnL4LvgR8bk3yJW3zWMa8wESRzYkvIe1SzehlJp2w_XpTNnw633c4FzgIXVMSU0rk3Tx_jRlhNAaSSJ7xEzSiQmQRY4yeohEhNIskSz7O0YX36_AGDR-hz2mzrXVv2y-8yN_xc9fbrsXFDi96W9v9wL91RWBLnLsGV53DTbPUvwYvrTO18R5PvnXbmnpAp8veOLvXQ8olOqt07c3VEcdocT-dTx6j2cvD0ySfRSUA9BEwKiAttWBQ6AK4KQuScGYyYUQqdRoOSHhV6hUkUlJYEUoqvSJaQ5pJkcEY3R5yN6772Rrfq3W3dW2oVCwkcE5YNqjIQVW6zntnKrVxttFupyhRw4IqLKiGBdVxwWC5OVisMeZfLkEKCLV_uO1sAQ</recordid><startdate>20211001</startdate><enddate>20211001</enddate><creator>Kachroo, Amit</creator><creator>Thornton, Collin A.</creator><creator>Sarker, Md. 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Arifur Rahman</au><au>Choi, Wooyeol</au><au>Bai, He</au><au>Song, Ickhyun</au><au>O'Hara, John F.</au><au>Ekin, Sabit</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Emulating UAV Motion by Utilizing Robotic Arm for mmWave Wireless Channel Characterization</atitle><jtitle>IEEE transactions on antennas and propagation</jtitle><stitle>TAP</stitle><date>2021-10-01</date><risdate>2021</risdate><volume>69</volume><issue>10</issue><spage>6691</spage><epage>6701</epage><pages>6691-6701</pages><issn>0018-926X</issn><eissn>1558-2221</eissn><coden>IETPAK</coden><abstract>In this article, millimeter-wave (mmWave) wireless channel characteristics (Doppler spread and path loss modeling) for unmanned aerial vehicle (UAV)-assisted communication is analyzed and studied by emulating the real UAV motion using a robotic arm. 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| subjects | Analytical models Anechoic chambers Atmospheric modeling Atmospheric models Channel emulation Communication Doppler Doppler effect Dryden wind model Gusts Manipulators Millimeter wave communication Millimeter waves millimeter-wave (mmWave) Noise levels path loss Robot arms Robots Statistical methods unmanned aerial vehicle (UAV) Unmanned aerial vehicles Wireless communication Wireless communication systems |
| title | Emulating UAV Motion by Utilizing Robotic Arm for mmWave Wireless Channel Characterization |
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