3D Non-Stationary Channel Measurement and Analysis for MaMIMO-UAV Communications

Unmanned aerial vehicles (UAVs) have gained popularity in the communications research community because of their versatility in placement and potential to extend the functions of communication networks. However, there remains a gap in existing works regarding measurement-verified stationarity analys...

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Published inIEEE transactions on vehicular technology Vol. 73; no. 5; pp. 6061 - 6072
Main Authors Colpaert, Achiel, Cui, Zhuangzhuang, Vinogradov, Evgenii, Pollin, Sofie
Format Journal Article
LanguageEnglish
Published New York IEEE 01.05.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN0018-9545
1939-9359
DOI10.1109/TVT.2023.3340447

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Abstract Unmanned aerial vehicles (UAVs) have gained popularity in the communications research community because of their versatility in placement and potential to extend the functions of communication networks. However, there remains a gap in existing works regarding measurement-verified stationarity analysis of the air-to-ground (A2G) Massive Multi-Input Multi-Output (MaMIMO) channel which plays an important role in realistic UAV deployment. In this article, we first design a UAV MaMIMO communication platform for channel acquisition. We then use the testbed to measure uplink Channel State Information (CSI) between a rotary-wing drone and a 64-element MaMIMO base station (BS). For characterization, we focus on multidimensional channel stationarity which is a fundamental metric in communication systems. Afterward, we present measurement results and analyze the channel statistics based on power delay profiles (PDPs) considering space, time, and frequency domains. We propose the stationary angle (SA) as a supplementary metric of stationary distance (SD) in the time domain. We analyze the coherence bandwidth and RMS delay spread for frequency stationarity. Finally, spatial correlations between elements are analyzed to indicate the spatial stationarity of the array. The space-time-frequency channel stationary characterization will benefit the physical layer design of MaMIMO-UAV communications.
AbstractList Unmanned aerial vehicles (UAVs) have gained popularity in the communications research community because of their versatility in placement and potential to extend the functions of communication networks. However, there remains a gap in existing works regarding measurement-verified stationarity analysis of the air-to-ground (A2G) Massive Multi-Input Multi-Output (MaMIMO) channel which plays an important role in realistic UAV deployment. In this article, we first design a UAV MaMIMO communication platform for channel acquisition. We then use the testbed to measure uplink Channel State Information (CSI) between a rotary-wing drone and a 64-element MaMIMO base station (BS). For characterization, we focus on multidimensional channel stationarity which is a fundamental metric in communication systems. Afterward, we present measurement results and analyze the channel statistics based on power delay profiles (PDPs) considering space, time, and frequency domains. We propose the stationary angle (SA) as a supplementary metric of stationary distance (SD) in the time domain. We analyze the coherence bandwidth and RMS delay spread for frequency stationarity. Finally, spatial correlations between elements are analyzed to indicate the spatial stationarity of the array. The space-time-frequency channel stationary characterization will benefit the physical layer design of MaMIMO-UAV communications.
Author Colpaert, Achiel
Cui, Zhuangzhuang
Pollin, Sofie
Vinogradov, Evgenii
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SubjectTerms Air-to-ground (A2G)
Antenna measurements
Antennas
Autonomous aerial vehicles
channel measurements
channel stationarity
Communication
Communication networks
Communications systems
Correlation
Drones
massive multi-input multi-output (MaMIMO) testbed
Measurement
Time domain analysis
Time-frequency analysis
unmanned aerial vehicle (UAV)
Unmanned aerial vehicles
Title 3D Non-Stationary Channel Measurement and Analysis for MaMIMO-UAV Communications
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