@inproceedings{887d0742ebf04a51a2fdb8c551999582,
title = "Compressive-sensing based beam and channel tracking with reconfigurable hybrid beamforming in mmwave MIMO OFDM systems",
abstract = "An efficient beam and channel tracking method is developed under a reconfigurable hybrid beamforming (R-HBF) architecture for wideband millimeter wave (mmWave) multiple input multiple output (MIMO) systems. With the R-HFB architecture, a multi-resolution compressive sensing (CS) method is proposed for initial beam and channel acquisitions in mmWave MIMO orthogonal frequency division multiplexing (OFDM) systems. With the initial beam and channel estimates, recursive schemes are further developed to track the angles of arrivals and departures and the channel coefficients of time-varying multiple channel paths. Simulation results show that the proposed method can significantly reduce the beam training time with a beam selection error rate less than 10^{-3} at typical vehicular speeds when the transmit power is greater than 10 dBm.",
author = "Wu, {Sau Hsuan} and Lu, {Guan Yu}",
year = "2019",
month = sep,
doi = "10.1109/VTCFall.2019.8891532",
language = "English",
series = "IEEE Vehicular Technology Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings",
address = "United States",
note = "90th IEEE Vehicular Technology Conference, VTC 2019 Fall ; Conference date: 22-09-2019 Through 25-09-2019",
}