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Beam Tracking Method Using Unscented Kalman Filter for UAV-Enabled NR MIMO-OFDM System with Hybrid Beamforming

Unmanned aerial vehicles (UAVs) and millimeter-wave frequencies play key roles in supporting 5G wireless communication systems. They expand the field of wireless communication by increasing the data capacities of communication systems and supporting high data rates. However, short wavelengths, owing...

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Bibliographic Details
Published in:KSII transactions on Internet and information systems 2023-01, Vol.17 (1), p.280
Main Authors: Sim, Yuna, Sin, Seungseok, Cho, Jihun, Moon, Sangmi, You, Young-Hwan, Kim, Cheol Hong, Hwang, Intae
Format: Article
Language:English
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Summary:Unmanned aerial vehicles (UAVs) and millimeter-wave frequencies play key roles in supporting 5G wireless communication systems. They expand the field of wireless communication by increasing the data capacities of communication systems and supporting high data rates. However, short wavelengths, owing to the high millimeter-wave frequencies can cause problems, such as signal attenuation and path loss. To address these limitations, research on high directional beamforming technologies continue to garner interest. Furthermore, owing to the mobility of the UAVs, it is essential to track the beam angle accurately to obtain full beamforming gain. This study presents a beam tracking method based on the unscented Kalman filter using hybrid beamforming. The simulation results reveal that the proposed beam tracking scheme improves the overall performance in terms of the mean-squared error and spectral efficiency. In addition, by expanding analog beamforming to hybrid beamforming, the proposed algorithm can be used even in multi-user and multi-stream environments to increase data capacity, thereby increasing utilization in new-radio multiple-input multiple-output orthogonal frequency-division multiplexing systems. Keywords: Beam tracking, hybrid beamforming, multiple-input multiple-output, orthogonal frequency diversity multiplexing, unscented Kalman filter.
ISSN:1976-7277
1976-7277
DOI:10.3837/tiis.2023.01.015