Subspace Tracking Algorithms for Millimeter Wave MIMO Channel Estimation with Hybrid Beamforming
Stefano Buzzi, Carmen D'Andrea

TL;DR
This paper introduces subspace tracking algorithms tailored for millimeter wave MIMO channel estimation with hybrid beamforming, demonstrating improved performance over existing methods.
Contribution
It develops novel subspace tracking algorithms adapted for hybrid beamforming in mmWave MIMO systems, explicitly considering the hybrid architecture.
Findings
Algorithms outperform existing methods in simulations
Effective in estimating channel singular vectors
Compatible with hybrid analog/digital beamforming
Abstract
This paper proposes the use of subspace tracking algorithms for performing MIMO channel estimation at millimeter wave (mmWave) frequencies. Using a subspace approach, we develop a protocol enabling the estimation of the right (resp. left) singular vectors at the transmitter (resp. receiver) side; then, we adapt the projection approximation subspace tracking with deflation (PASTd) and the orthogonal Oja (OOJA) algorithms to our framework and obtain two channel estimation algorithms. The hybrid analog/digital nature of the beamformer is also explicitly taken into account at the algorithm design stage. Numerical results show that the proposed estimation algorithms are effective, and that they perform better than two relevant competing alternatives available in the open literature.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMillimeter-Wave Propagation and Modeling · Advanced MIMO Systems Optimization · Microwave Engineering and Waveguides
