TY - GEN
T1 - Wideband Channel Tracking for Millimeter Wave Massive Mimo Systems with Hybrid Beamforming Reception
AU - Alexandropoulos, George C.
AU - Vlachos, Evangelos
AU - Thompson, John
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/4/9
Y1 - 2020/4/9
N2 - Millimeter Wave (mmWave) massive Multiple Input Multiple Output (MIMO) channel tracking is a challenging task with Hybrid analog and digital BeamForming (HBF) reception architectures. The wireless channel can only be spatially sampled with directive analog beams, which results in lengthy training periods when beam codebooks are large. In this paper, we capitalize on a recently proposed HBF architecture enabling mmWave massive MIMO channel estimation with short beam training overhead, and present a matrix-completion-based channel tracking technique for time correlated HBF receivers. The considered channel tracking problem is formulated as a constrained multi-objective optimization problem incorporating the low rank and group-sparse properties of the mmWave channel as well as a popular model for its time correlation. We present an efficient algorithm for this estimation problem that is based on the alternating direction method of multipliers. Comparisons of the proposed approach over representative state-of-the-art techniques showcase the relation between the channel time correlation coefficient and the amount of beam training needed for acceptable channel estimation performance.
AB - Millimeter Wave (mmWave) massive Multiple Input Multiple Output (MIMO) channel tracking is a challenging task with Hybrid analog and digital BeamForming (HBF) reception architectures. The wireless channel can only be spatially sampled with directive analog beams, which results in lengthy training periods when beam codebooks are large. In this paper, we capitalize on a recently proposed HBF architecture enabling mmWave massive MIMO channel estimation with short beam training overhead, and present a matrix-completion-based channel tracking technique for time correlated HBF receivers. The considered channel tracking problem is formulated as a constrained multi-objective optimization problem incorporating the low rank and group-sparse properties of the mmWave channel as well as a popular model for its time correlation. We present an efficient algorithm for this estimation problem that is based on the alternating direction method of multipliers. Comparisons of the proposed approach over representative state-of-the-art techniques showcase the relation between the channel time correlation coefficient and the amount of beam training needed for acceptable channel estimation performance.
KW - alternating direction method of multipliers (ADMM)
KW - Channel tracking
KW - massive multiple-input multiple-output (MIMO)
KW - millimeter wave communications
UR - http://www.scopus.com/inward/record.url?scp=85089216084&partnerID=8YFLogxK
U2 - 10.1109/ICASSP40776.2020.9053440
DO - 10.1109/ICASSP40776.2020.9053440
M3 - Conference contribution
AN - SCOPUS:85089216084
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 8698
EP - 8702
BT - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers
T2 - 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
Y2 - 4 May 2020 through 8 May 2020
ER -