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Electrical Engineering and Systems Science > Signal Processing

arXiv:1804.08640 (eess)
[Submitted on 23 Apr 2018]

Title:Adaptive Beam Tracking with the Unscented Kalman Filter for Millimeter Wave Communication

Authors:Stephen G. Larew, David J. Love
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Abstract:Millimeter wave (mmWave) communication links for 5G cellular technology require high beamforming gain to overcome channel impairments and achieve high throughput. While much work has focused on estimating mmWave channels and designing beamforming schemes, the time dynamic nature of mmWave channels quickly renders estimates stale and increases sounding overhead. We model the underlying time dynamic state space of mmWave channels and design sounding beamformers suitable for tracking in a Kalman filtering framework. Given an initial channel estimate, filtering efficiently leads to refined estimates and allows forward prediction for higher sustained beamforming gain during data transmission. From tracked prior channel estimates, adaptively chosen optimal and constrained suboptimal beams reduce sounding overhead while minimizing estimation error.
Comments: Submitted to IEEE Signal Processing Letters
Subjects: Signal Processing (eess.SP); Information Theory (cs.IT)
Cite as: arXiv:1804.08640 [eess.SP]
  (or arXiv:1804.08640v1 [eess.SP] for this version)
  https://doi.org/10.48550/arXiv.1804.08640
Related DOI: https://doi.org/10.1109/LSP.2019.2944255

Submission history

From: Stephen Larew [view email]
[v1] Mon, 23 Apr 2018 18:00:38 UTC (123 KB)
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