Drone-Yer Haberlesmesinde Kanal Olcumleri ve Modellemesi

Okan Erturk; Kutay Bolat; Ayse Betul Buyuksar; A. Doruk Baskan; Ibrahim Altunbas

doi:10.1109/SIU49456.2020.9302062

Drone-Yer Haberlesmesinde Kanal Olcumleri ve Modellemesi

Translated title of the contribution: Channel Measurements and Modeling in Drone-to-Ground Communications

Okan Erturk, Kutay Bolat, Ayse Betul Buyuksar, A. Doruk Baskan, Ibrahim Altunbas

Department of Electronics and Communication Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

The drones, which are expected to take part in next-generation communication systems, are used in many elds such as military, commercial and disaster management. The demand for drone use has been increasing day by day due to their exible design and easy installation that is customized for various applications. Accurate modeling of drone channels is essential for creating, development, and optimization of the drone-to-ground communication systems. In this study, the statistical properties of drone-to-ground channels are investigated via the measurements based on the received signal strength indicator (RSS/RSSI) provided by the IEEE 802.11n Wi-Fi network standard. Using the measurements, the path loss exponent of the drone-ground channels is estimated. In addition, Rician, Nakagami-m and Log-normal distributions are adapted to the measurements obtained for different heights of the drone with the help of the maximum likelihood decision rule and the performance of these probability distributions in modeling the measured drone-ground channel statistics are compared with each other.

Translated title of the contribution	Channel Measurements and Modeling in Drone-to-Ground Communications
Original language	Turkish
Title of host publication	2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728172064
DOIs	https://doi.org/10.1109/SIU49456.2020.9302062
Publication status	Published - 5 Oct 2020
Event	28th Signal Processing and Communications Applications Conference, SIU 2020 - Gaziantep, Turkey Duration: 5 Oct 2020 → 7 Oct 2020

Publication series

Name	2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings

Conference

Conference	28th Signal Processing and Communications Applications Conference, SIU 2020
Country/Territory	Turkey
City	Gaziantep
Period	5/10/20 → 7/10/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Access to Document

10.1109/SIU49456.2020.9302062

Cite this

Erturk, O., Bolat, K., Buyuksar, A. B., Baskan, A. D., & Altunbas, I. (2020). Drone-Yer Haberlesmesinde Kanal Olcumleri ve Modellemesi. In 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings Article 9302062 (2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU49456.2020.9302062

Erturk, Okan ; Bolat, Kutay ; Buyuksar, Ayse Betul et al. / Drone-Yer Haberlesmesinde Kanal Olcumleri ve Modellemesi. 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. (2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings).

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abstract = "The drones, which are expected to take part in next-generation communication systems, are used in many elds such as military, commercial and disaster management. The demand for drone use has been increasing day by day due to their exible design and easy installation that is customized for various applications. Accurate modeling of drone channels is essential for creating, development, and optimization of the drone-to-ground communication systems. In this study, the statistical properties of drone-to-ground channels are investigated via the measurements based on the received signal strength indicator (RSS/RSSI) provided by the IEEE 802.11n Wi-Fi network standard. Using the measurements, the path loss exponent of the drone-ground channels is estimated. In addition, Rician, Nakagami-m and Log-normal distributions are adapted to the measurements obtained for different heights of the drone with the help of the maximum likelihood decision rule and the performance of these probability distributions in modeling the measured drone-ground channel statistics are compared with each other.",

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author = "Okan Erturk and Kutay Bolat and Buyuksar, {Ayse Betul} and Baskan, {A. Doruk} and Ibrahim Altunbas",

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Erturk, O, Bolat, K, Buyuksar, AB, Baskan, AD & Altunbas, I 2020, Drone-Yer Haberlesmesinde Kanal Olcumleri ve Modellemesi. in 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings., 9302062, 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 28th Signal Processing and Communications Applications Conference, SIU 2020, Gaziantep, Turkey, 5/10/20. https://doi.org/10.1109/SIU49456.2020.9302062

Drone-Yer Haberlesmesinde Kanal Olcumleri ve Modellemesi. / Erturk, Okan; Bolat, Kutay; Buyuksar, Ayse Betul et al.
2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. 9302062 (2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Drone-Yer Haberlesmesinde Kanal Olcumleri ve Modellemesi

AU - Erturk, Okan

AU - Bolat, Kutay

AU - Buyuksar, Ayse Betul

AU - Baskan, A. Doruk

AU - Altunbas, Ibrahim

PY - 2020/10/5

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N2 - The drones, which are expected to take part in next-generation communication systems, are used in many elds such as military, commercial and disaster management. The demand for drone use has been increasing day by day due to their exible design and easy installation that is customized for various applications. Accurate modeling of drone channels is essential for creating, development, and optimization of the drone-to-ground communication systems. In this study, the statistical properties of drone-to-ground channels are investigated via the measurements based on the received signal strength indicator (RSS/RSSI) provided by the IEEE 802.11n Wi-Fi network standard. Using the measurements, the path loss exponent of the drone-ground channels is estimated. In addition, Rician, Nakagami-m and Log-normal distributions are adapted to the measurements obtained for different heights of the drone with the help of the maximum likelihood decision rule and the performance of these probability distributions in modeling the measured drone-ground channel statistics are compared with each other.

AB - The drones, which are expected to take part in next-generation communication systems, are used in many elds such as military, commercial and disaster management. The demand for drone use has been increasing day by day due to their exible design and easy installation that is customized for various applications. Accurate modeling of drone channels is essential for creating, development, and optimization of the drone-to-ground communication systems. In this study, the statistical properties of drone-to-ground channels are investigated via the measurements based on the received signal strength indicator (RSS/RSSI) provided by the IEEE 802.11n Wi-Fi network standard. Using the measurements, the path loss exponent of the drone-ground channels is estimated. In addition, Rician, Nakagami-m and Log-normal distributions are adapted to the measurements obtained for different heights of the drone with the help of the maximum likelihood decision rule and the performance of these probability distributions in modeling the measured drone-ground channel statistics are compared with each other.

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KW - Log-normal

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KW - Rician

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BT - 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 28th Signal Processing and Communications Applications Conference, SIU 2020

Y2 - 5 October 2020 through 7 October 2020

ER -

Erturk O, Bolat K, Buyuksar AB, Baskan AD, Altunbas I. Drone-Yer Haberlesmesinde Kanal Olcumleri ve Modellemesi. In 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. 9302062. (2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings). doi: 10.1109/SIU49456.2020.9302062

Drone-Yer Haberlesmesinde Kanal Olcumleri ve Modellemesi

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