Multi-Armed Bandit Beam Alignment and Tracking for Mobile Millimeter Wave Communications

We propose a novel beam alignment and tracking algorithm for time-varying millimeter wave channels with a dynamic channel support. Millimeter wave beam alignment is challenging due to the expected large number of antennas. A multi-armed bandit training beam selection policy is used to balance explor...

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Veröffentlicht in:	IEEE communications letters 2019-07, Vol.23 (7), p.1244-1248
Hauptverfasser:	Booth, Matthew B., Suresh, Vinayak, Michelusi, Nicolo, Love, David J.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Alignment Array signal processing Bayes methods Bayesian analysis beam tracking Beamforming Beams (radiation) Channel estimation Kalman filter Kalman filters Machine learning Millimeter wave Millimeter waves Mobile communication systems Multi-armed bandit problems multi-armed bandits Receivers sparse Bayesian learning Tracking Training Transmitters
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