IET Communications

2017

DOI: 10.1049/iet-com.2016.1360

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Low overhead channel tracking strategy for millimetre wave multiple‐input multiple‐output system

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Cited by 4 publications

References 21 publications

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Training Beam Sequence Optimization for Millimeter Wave MIMO Tracking Systems

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Shirvanimoghaddam

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et al. 2018

2018 IEEE International Conference on Communications (ICC)

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Training Beam Sequence Optimization for Millimeter Wave MIMO Tracking Systems

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Shirvanimoghaddam

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et al. 2018

2018 IEEE International Conference on Communications (ICC)

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Adaptive Beam Tracking With the Unscented Kalman Filter for Millimeter Wave Communication

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2019

IEEE Signal Process. Lett.

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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.

Sparse, Group-Sparse, and Online Bayesian Learning Aided Channel Estimation for Doubly-Selective mmWave Hybrid MIMO OFDM Systems

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et al. 2021

IEEE Trans. Commun.

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