Compressive Beam and Channel Tracking with Reconfigurable Hybrid Beamforming in mmWave MIMO OFDM Systems

Sau Hsuan Wu, Guan Yu Lu

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

An efficient beam and channel acquisition and tracking scheme is developed under a reconfigurable hybrid beamforming (R-HBF) architecture for wideband millimeter wave (mmWave) multiple input multiple output (MIMO) systems. Under such an R-HBF, a hierarchical multi-resolution beam scanning and space-frequency compressive sensing method is proposed to achieve fast beam and channel acquisitions in mmWave MIMO orthogonal frequency division multiplexing (OFDM) systems. With the initial frequency-domain beam space channel estimates, Kalman-based algorithms are further developed to track the transmit and receive beamforming directions and the channel coefficients of the sparse propagation paths in mmWave mobile channels. Simulations show that the proposed method can greatly reduce the beam training time, and that the channel capacity evaluated with the estimated channels is only 2 dB inferior to the one with ideal channels. Moreover, the beam selection error rates are less than 10-3 in typical urban mmWave mobile channels and traveling speeds even if the transmit power is only 10 dBm.

Original languageEnglish
Pages (from-to)1
Number of pages1
JournalIEEE Transactions on Wireless Communications
DOIs
StateAccepted/In press - 2022

Keywords

  • Channel estimation
  • Millimeter wave communication
  • MIMO communication
  • OFDM
  • Phased arrays
  • Radar tracking
  • Radio frequency

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