Deep Learning Enabled Beam Tracking for Non-Line of Sight Millimeter Wave Communications

Deep Learning Enabled Beam Tracking for Non-Line of Sight Millimeter Wave Communications

To solve the complex beam alignment issue in non-line-of-sight (NLOS) millimeter wave communications, this paper presents a deep neural network (DNN) based procedure to predict the angle of arrival (AOA) and angle of departure (AOD) both in terms of azimuth and elevation, i.e., AAOA/AAOD and EAOA/EA...

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Bibliographic Details
Main Authors: Ruiyu Wang, Paulo Valente Klaine, Oluwakayode Onireti, Yao Sun, Muhammad Ali Imran, Lei Zhang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Open Journal of the Communications Society
Subjects:
Deep learning
mmWave
NLOS
trajectory prediction
estimation
Online Access:https://ieeexplore.ieee.org/document/9478921/

Internet

https://ieeexplore.ieee.org/document/9478921/

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