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

Juseong Park, Seunghwan Baek, Jihwan Moon, Inkyu Lee

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)13413-13417
Number of pages5
JournalIEEE Transactions on Vehicular Technology
Volume70
Issue number12
DOIs
Publication statusPublished - 2021 Dec 1

Keywords

  • Bayesian inference
  • Beam tracking
  • millimeter-wave communication

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Applied Mathematics

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