Machine learning-assisted direction-of-arrival accuracy enhancement technique using oversized lens-loaded cavity

Machine learning-assisted direction-of-arrival accuracy enhancement technique using oversized lens-loaded cavity

This paper presents a framework for achieving machine learning (ML)-assisted direction-of-arrival (DoA) accuracy enhancement using a millimetre-wave (mmWave) dynamic aperture. The technique used for the enhanced DoA estimation accuracy leverages an over-sized lens-loaded cavity antenna connected to...

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Bibliographic Details
Main Authors: Abbasi, M.A.B (Author), Akinsolu, M.O (Author), Cotton, S.L (Author), Fusco, V.F (Author), Imran, M.A (Author), Khalily, M. (Author), Liu, B. (Author), Yurduseven, O. (Author)
Format: Article
Language:English
Published: John Wiley and Sons Inc 2022
Subjects:
Accuracy enhancement
antennas
B5G mobile communication
channel estimation
Computer hardware
Direction of arrival
Direction of arrival estimation
Directionof-arrival (DOA)
diversity reception
lens antennas
Loaded cavity
Machine learning
Millimeter waves
Mixing
Mixing mechanisms
Mobile communications
Mode mixing
Network layers
Radiation mode
Receiving antennas
Wave dynamics
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