Robust Beam Tracking Algorithm for mmWave MIMO Systems in Mobile Environments

Kim, Seonyong; Han, Hyungsik; Kim, Namshik; Park, Hyuncheol

doi:10.1109/vtcfall.2019.8891561

Cited by 12 publications

(7 citation statements)

References 9 publications

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“…The developed algorithm was compared with the state-of-the-art power-based AOA estimation methods that also use a single digital port. They were the Auxiliary Beam technique (AuxBeam) [14], [15] and Adaptive Compressed Sensing (ACS) [16].…”

Section: Simulation Resultsmentioning

confidence: 99%

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Subspace-based AOA estimation in mmWave NR system using power measurement with a single-port antenna array

Shmonin¹,

Kuptsov²,

Trushkov³

et al. 2022

Preprint

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The paper is dedicated to the multipath angle of arrival (AOA) estimation problem in millimeter wave (mmWave) 5G NR communication system. The case of a phased antenna array with a single digital port is considered. In this scenario, the conventional highly accurate subspace-based algorithms cannot be applied because of hardware restrictions. We proposed a novel subspace-based algorithm called power-based root minimal polynomial method (PR-MPM) that uses the spatial power spectrum to get an approximation of the signal correlation matrix. The power spectrum is measured via the conventional beam sweeping procedure over a finite number of directions. The efficiency of the proposed method is studied using the high-realistic ray-tracing-based channel model applied in mmWave IEEE 802.11ay standard. Simulation results show that AOAs can be precisely estimated using only single-port power measurement.

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Section: Simulation Resultsmentioning

confidence: 99%

“…For the selected BS's beam the best "neighbour" of the UE's beam was taken to calculate the metric and estimate AOA. To increase accuracy it may have required performing some additional power measurements in accordance with [15]. Thus, it is how the main path AOA was estimated.…”

Section: Simulation Resultsmentioning

confidence: 99%

Subspace-based AOA estimation in mmWave NR system using power measurement with a single-port antenna array

Shmonin¹,

Kuptsov²,

Trushkov³

et al. 2022

Preprint

View full text Add to dashboard Cite

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“…For this reason, [13] proposed unscented Kalman filter (UKF) with the intractability of recursive Bayesian estimation that does not depend on a Jacobian matrix and presented that the UKF is a better tracking scheme compared to that of the EKF. According to [14], based on extended Kalman filter (EKF) incorporating a monopulse signal is an effective beam tracking scheme for the moving object in the unmanned aerial vehicles (UAVs) to manage the challenges of mobility and frequent channel disconnection and also shown that it is even better compared to other conventional schemes [15][16][17]. By considering UAV position and attitude estimation with machine learning (ML), an efficient beamwidth control based beam tracking approach was proposed in [18,19] for optimal beam pair selection.…”

Section: A Related Workmentioning

confidence: 99%

“…It has been shown that in multipath channels there are multiple local optima and this scheme may converge to a local optima. This problem was addressed by [54] through iterating their algorithm multiple times in which each iteration starts from the previous solution. This may increase the computational complexity and latency of the searching algorithm.…”

Section: A Related Workmentioning

confidence: 99%

Allied Power Constraint Optimization and Optimal Beam Tracking Schemes for Mobile mmWave Massive MIMO Communications

Ghosh¹,

Singh

Hacı³

et al. 2021

IEEE Access

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“…As 5G mobile communication using millimeter wave has become a hot topic, there is a good amount of previous work on beam management for millimeter wave considering mobile environment. In [13], [14], studied and proposed beam tracking algorithm in mobile environment by using extended Kalman filter to improve beam alignment accuracy. Some previous work considered location aided beam management considering mobility.…”

Section: Introductionmentioning

confidence: 99%

Beam Management in Millimeter-Wave Communications for 5G and Beyond

et al. 2020

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Massive MIMO is one of the promising techniques to improve spectral efficiency and network performance for reaching its targeted multi-gigabit throughput in 5G systems. For 5G New Radio (NR) systems, one of the key differences compared to 4G systems is the utilization of high frequency millimeter wave (mmWave) bands in addition to sub-6GHz bands. To keep the complexity and implementation cost low, hybrid analog-digital beam-forming with large-scale antenna array has become a common design approach to address the issue of higher propagation loss as well as to improve spectral efficiency in mmWave communication in 5G NR. The 5G NR standard is designed to adapt to different beam-forming architecture and deployment scenarios. This paper provides the overview on beam management procedure according to the current 5G standardization progress. We discuss some major challenges of millimeterwave communications encountered in the current 5G NR standard and present some expected enhancements considered for the future beyond-5G standard. INDEX TERMS 5G NR systems, beam management, physical layer, beyond 5G, hybrid beamforming, AI based beam management.

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Robust Beam Tracking Algorithm for mmWave MIMO Systems in Mobile Environments

Cited by 12 publications

References 9 publications

Subspace-based AOA estimation in mmWave NR system using power measurement with a single-port antenna array

Subspace-based AOA estimation in mmWave NR system using power measurement with a single-port antenna array

Allied Power Constraint Optimization and Optimal Beam Tracking Schemes for Mobile mmWave Massive MIMO Communications

Beam Management in Millimeter-Wave Communications for 5G and Beyond

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