Adaptive Filters Versus Machine Learning Based Beam Tracking Techniques for Millimeter-Wave Wireless Communications Systems

Adaptive Filters Versus Machine Learning Based Beam Tracking Techniques for Millimeter-Wave Wireless Communications Systems

This work compares the data-based using (bidirectional long short-term memory (BiLSTM)) and model-based using (extended Kalman filter (EKF) and least mean squares (LMS)) strategies to track the communication beams for millimeter wave (mm-wave) vehicular communications. This work utilizes the Deep MI...

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Bibliographic Details
Main Authors: Ruaa Shallal Abbas Anooz, Jafar Pourrostam, Mohanad Al-Ibadi
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Vehicular mm-wave communication
beam tracking
adaptive filters
machine learning
BiLSTM
Online Access:https://ieeexplore.ieee.org/document/10744015/
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https://ieeexplore.ieee.org/document/10744015/

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