KM Learning for Millimeter-Wave Beam Alignment and Tracking: Predictability and Interpretability

KM Learning for Millimeter-Wave Beam Alignment and Tracking: Predictability and Interpretability

A data representation technique dubbed Kolmogorov model (KM), has been applied to the beam alignment problem in large-dimensional antenna systems. The previous learning-based beam alignment solely focused on utilizing the predictive power of KM, i.e., the capability of predicting the outcome of rand...

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Bibliographic Details
Main Authors: Qiyou Duan, Taejoon Kim, Hadi Ghauch
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Beam tracking
Kolmogorov model (KM)
discrete monotonic optimization (DMO)
dual optimization
predictability
interpretability
Online Access:https://ieeexplore.ieee.org/document/9521541/

Internet

https://ieeexplore.ieee.org/document/9521541/

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