Millimeter Wave (mmWave) massive Multiple Input Multi- ple Output (MIMO) channel tracking is a challenging task with Hybrid analog and digital BeamForming (HBF) re- ception architectures. The wireless channel can only be spatially sampled with directive analog beams, which re- sults 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 track- ing 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 pop- ular 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.
The figure demonstrates that the proposed technique achieves near-optimal performance with significantly reduced training overhead, converging faster and achieving lower NMSE than OMP and AdaOMP for time-varying channels.
The results show that the proposed technique maintains low NMSE and achieves high achievable spectral efficiency even with short training sequences, highlighting its effectiveness in reducing beam training overhead while preserving channel estimation accuracy.