Grid-Based Bayesian Beam Tracking With Multiple Observations for Millimeter Wave Channels

In this paper, we study a beam tracking problem for millimeter wave (mmWave) channels in massive multiple-input and multiple-output communication systems. We formulate the beam tracking problem as a stochastic filtering problem by modeling the dynamic state equation and the observation equation. The...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 2021-12, Vol.70 (12), p.13413-13417
Main Authors: Park, Juseong, Baek, Seunghwan, Moon, Jihwan, Lee, Inkyu
Format: Article
Language:English
Subjects:
Algorithms
Bayes methods
Bayesian analysis
Bayesian inference
Beam tracking
Channel estimation
Channels
Communications systems
Equations of state
Mathematical models
Millimeter wave communication
Millimeter waves
Tracking problem
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Summary:In this paper, we study a beam tracking problem for millimeter wave (mmWave) channels in massive multiple-input and multiple-output communication systems. We formulate the beam tracking problem as a stochastic filtering problem by modeling the dynamic state equation and the observation equation. Then, given prior information of the channel, we propose an efficient grid-based Bayesian beam tracking algorithm by leveraging the sparsity of the mmWave channel. Our proposed algorithm examines neighboring transmit and receive beam pairs and exploits multiple observations on the angular domain representation in the sense of the Bayesian statistics. Numerical results show that the proposed Bayesian method with multiple observations outperforms conventional schemes in terms of both the beam tracking accuracy and computational complexity.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2021.3120516