Method for Detection of Airborne UEs based on LTE Radio Measurements

Jeroen Wigard; Rafhael Medeiros de Amorim; Huan Cong Nguyen; István Kovács; Preben Elgaard Mogensen

doi:10.1109/PIMRC.2017.8292313

Method for Detection of Airborne UEs based on LTE Radio Measurements

Jeroen Wigard, Rafhael Medeiros de Amorim, Huan Cong Nguyen, István Kovács, Preben Elgaard Mogensen

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

3 Citations (Scopus)

Abstract

Unmanned Aerial Vehicles (UAVs) are expected to be connected through cellular networks. As the radio characteristics are different for airborne UEs compared to terrestrial UEs, it is beneficial to identify whether a UE is airborne (on a UAV) or on the ground, such that interference and mobility management can be optimized for UAVs separately from terrestrial UEs. In this paper, we present a classification algorithm using existing LTE UE radio measurements to identify whether a UE is airborne or terrestrial. The method is verified with LTE measurements made in a rural area at different heights, including terrestrial measurements and it is shown that the method in 3 out of the 4 different measurement cases can detect a UE to be airborne with 99% likelihood, while the fourth case still can classify a UE correctly in 95% of the cases. The right classification can further be improved by taking multiple consecutive samples into account before making a classification decision.

Original language	English
Title of host publication	IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)
Publisher	IEEE
Publication date	Oct 2017
ISBN (Print)	978-1-5386-3529-2
ISBN (Electronic)	978-1-5386-3531-5
DOIs	https://doi.org/10.1109/PIMRC.2017.8292313
Publication status	Published - Oct 2017
Event	PIMRC 2017 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications - Montreal, Canada Duration: 8 Oct 2017 → 13 Oct 2017 http://pimrc2017.ieee-pimrc.org/

Conference

Conference	PIMRC 2017 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications
Country/Territory	Canada
City	Montreal
Period	08/10/2017 → 13/10/2017
Internet address	http://pimrc2017.ieee-pimrc.org/

Series	I E E E International Symposium Personal, Indoor and Mobile Radio Communications
ISSN	2166-9570

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10.1109/PIMRC.2017.8292313

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3 Citations
1 Book chapter
1 Journal article

Performance Enhancements for LTE-Connected UAVs: Experiments and Simulations
Amorim, R. M. D., Kovacs, I., Wigard, J. & Sørensen, T. B., 2021, UAV Communications for 5G and Beyond. Zeng, Y., Guvenc, I., Zhang, R., Geraci, G. & W. Matolak, D. (eds.). 1 ed. Wiley, p. 139-161 23 p.
Research output: Contribution to book/anthology/report/conference proceeding › Book chapter › Research › peer-review
How to ensure reliable connectivity for aerial vehicles over cellular networks
Nguyen, H. C., Amorim, R. M. D., Wigard, J., Kovács, I., Bundgaard Sørensen, T. & Mogensen, P. E., 22 Feb 2018, In: IEEE Access. 6, p. 12304-12317 14 p.
Research output: Contribution to journal › Journal article › Research › peer-review

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135 Citations (Scopus)

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Cite this

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title = "Method for Detection of Airborne UEs based on LTE Radio Measurements",

abstract = "Unmanned Aerial Vehicles (UAVs) are expected to be connected through cellular networks. As the radio characteristics are different for airborne UEs compared to terrestrial UEs, it is beneficial to identify whether a UE is airborne (on a UAV) or on the ground, such that interference and mobility management can be optimized for UAVs separately from terrestrial UEs. In this paper, we present a classification algorithm using existing LTE UE radio measurements to identify whether a UE is airborne or terrestrial. The method is verified with LTE measurements made in a rural area at different heights, including terrestrial measurements and it is shown that the method in 3 out of the 4 different measurement cases can detect a UE to be airborne with 99% likelihood, while the fourth case still can classify a UE correctly in 95% of the cases. The right classification can further be improved by taking multiple consecutive samples into account before making a classification decision.",

author = "Jeroen Wigard and Amorim, {Rafhael Medeiros de} and Nguyen, {Huan Cong} and Istv{\'a}n Kov{\'a}cs and Mogensen, {Preben Elgaard}",

year = "2017",

month = oct,

doi = "10.1109/PIMRC.2017.8292313",

language = "English",

isbn = "978-1-5386-3529-2",

series = "I E E E International Symposium Personal, Indoor and Mobile Radio Communications",

booktitle = "IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)",

publisher = "IEEE",

address = "United States",

note = "PIMRC 2017 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC ; Conference date: 08-10-2017 Through 13-10-2017",

url = "http://pimrc2017.ieee-pimrc.org/",

}

Wigard, J, Amorim, RMD, Nguyen, HC, Kovács, I & Mogensen, PE 2017, Method for Detection of Airborne UEs based on LTE Radio Measurements. in IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, I E E E International Symposium Personal, Indoor and Mobile Radio Communications, PIMRC 2017 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Montreal, Canada, 08/10/2017. https://doi.org/10.1109/PIMRC.2017.8292313

Method for Detection of Airborne UEs based on LTE Radio Measurements. / Wigard, Jeroen; Amorim, Rafhael Medeiros de; Nguyen, Huan Cong et al.
IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, 2017. (I E E E International Symposium Personal, Indoor and Mobile Radio Communications).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Method for Detection of Airborne UEs based on LTE Radio Measurements

AU - Wigard, Jeroen

AU - Amorim, Rafhael Medeiros de

AU - Nguyen, Huan Cong

AU - Kovács, István

AU - Mogensen, Preben Elgaard

PY - 2017/10

Y1 - 2017/10

N2 - Unmanned Aerial Vehicles (UAVs) are expected to be connected through cellular networks. As the radio characteristics are different for airborne UEs compared to terrestrial UEs, it is beneficial to identify whether a UE is airborne (on a UAV) or on the ground, such that interference and mobility management can be optimized for UAVs separately from terrestrial UEs. In this paper, we present a classification algorithm using existing LTE UE radio measurements to identify whether a UE is airborne or terrestrial. The method is verified with LTE measurements made in a rural area at different heights, including terrestrial measurements and it is shown that the method in 3 out of the 4 different measurement cases can detect a UE to be airborne with 99% likelihood, while the fourth case still can classify a UE correctly in 95% of the cases. The right classification can further be improved by taking multiple consecutive samples into account before making a classification decision.

AB - Unmanned Aerial Vehicles (UAVs) are expected to be connected through cellular networks. As the radio characteristics are different for airborne UEs compared to terrestrial UEs, it is beneficial to identify whether a UE is airborne (on a UAV) or on the ground, such that interference and mobility management can be optimized for UAVs separately from terrestrial UEs. In this paper, we present a classification algorithm using existing LTE UE radio measurements to identify whether a UE is airborne or terrestrial. The method is verified with LTE measurements made in a rural area at different heights, including terrestrial measurements and it is shown that the method in 3 out of the 4 different measurement cases can detect a UE to be airborne with 99% likelihood, while the fourth case still can classify a UE correctly in 95% of the cases. The right classification can further be improved by taking multiple consecutive samples into account before making a classification decision.

U2 - 10.1109/PIMRC.2017.8292313

DO - 10.1109/PIMRC.2017.8292313

M3 - Article in proceeding

SN - 978-1-5386-3529-2

T3 - I E E E International Symposium Personal, Indoor and Mobile Radio Communications

BT - IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

PB - IEEE

T2 - PIMRC 2017 - IEEE International Symposium on Personal, Indoor and Mobile Radio Communications

Y2 - 8 October 2017 through 13 October 2017

ER -

Method for Detection of Airborne UEs based on LTE Radio Measurements

Abstract

Conference

Access to Document

AUB Link

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Research output

Performance Enhancements for LTE-Connected UAVs: Experiments and Simulations

How to ensure reliable connectivity for aerial vehicles over cellular networks

Cite this