Optimal Precoders for Tracking the AoD and AoA of a mmWave Path

Garcia, Nil; Wymeersch, Henk; Slock, Dirk

doi:10.1109/tsp.2018.2870368

Cited by 61 publications

(75 citation statements)

References 46 publications

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“…However, in the multilinear SVD, the column, row, and fiber spaces can have different ranks. For (16), the column rank is the number of columns in U (1) , the row rank is the number of columns in U (2) , and the fiber rank is the number of columns in U (3) .…”

Section: A the Multilinear Singular Value Decompositionmentioning

confidence: 99%

Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation

Ruble

Güvenç

2020

IEEE Access

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Fifth generation (5G) cellular standards are set to utilize millimeter wave (mmWave) frequencies, which enable data speeds greater than 10 Gbps and sub-centimeter localization accuracy. These capabilities rely on accurate estimates of the channel parameters, which we define as the angle of arrival, angle of departure, and path distance for each path between the transmitter and receiver. Estimating the channel parameters in a computationally efficient manner poses a challenge because it requires estimation of parameters from a high-dimensional measurement -particularly for multi-carrier systems since each subcarrier must be estimated separately. Additionally, channel parameter estimation must be able to handle hybrid beamforming, which uses a combination of digital and analog beamforming to reduce the number of required analog to digital converters. This paper introduces a channel parameter estimation technique based on the multilinear singular value decomposition (MSVD), a tensor analog of the singular value decomposition, for massive multiple input multiple output (MIMO) multi-carrier systems with hybrid beamforming. The MSVD tensor estimation approach provides a computationally efficient method and is shown to closely match the Cramer-Rao bound (CRB) of parameter estimates through simulations. Limitations of channel parameter estimation and communication waveform effects are also studied.

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Section: A the Multilinear Singular Value Decompositionmentioning

confidence: 99%

Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation

Ruble

Güvenç

2020

IEEE Access

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“…Previously, the robust beamformer design based on the minimization of the Cramér-Rao bound (CRB) of the AOA/AOD for maximum angular spreads σ max θ0 and σ max φ0 was proposed in [62]. We propose a much simpler approach named as heuristic beamformers in beamspace.…”

Section: Heuristic Beamformer For Trackingmentioning

confidence: 99%

“…The expectations and unbiased constraints in R B can be replaced using the equivalent terms from the FIM. Consequently, the robust beamformer F MS = F RF,MS F BB,MS is designed for maximum angular spreads σ max θ0 and σ max φ0 within the observation time T ob [62].…”

Section: A Beamformer Design Problemmentioning

confidence: 99%

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Tracking Position and Orientation Through Millimeter Wave Lens MIMO in 5G Systems

Shahmansoori

Uguen

Destino

et al. 2019

IEEE Signal Process. Lett.

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Millimeter wave signals and large antenna arrays are considered enabling technologies for future 5G networks. Despite their benefits for achieving high data rate communications, their potential advantages for tracking of the location of the user terminals are largely undiscovered. In this paper, we propose a novel support detection-based channel training method for frequency selective millimeter-wave (mm-wave) multiple-input-multiple-output system with lens antenna arrays. We show that accurate position and orientation estimation and tracking is possible using signals from a single transmitter with lens antenna arrays. Particularly, the beamspace channel estimation is formulated as two sparse signal recovery problems in the downlink and uplink for the estimation of angle-of-arrival, angle-of-departure, and timeof-arrival. The proposed method offers a higher sparse detection probability compared to the compressed sensing based solutions. Finally, a joint heuristic beamformer design and user position and orientation tracking approach are proposed based on initial estimation of channel parameters obtained in the training phase.

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“…This analog beamforming solution has been standardized by IEEE 802.11ad [5] and IEEE 802. 15.3c [6], and is actively discussed by several 5G industrial organizations [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Analog beam tracking in linear antenna arrays: Convergence, optimality, and performance

Li¹,

Sun

Xiao

et al. 2017

2017 51st Asilomar Conference on Signals, Systems, and Computers

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The directionality of millimeter-wave (mmWave) communications creates a significant challenge in serving fastmoving mobile terminals on, e.g., high-speed vehicles, trains, and UAVs. This challenge is exacerbated in mmWave systems using analog antenna arrays, because of the inherent non-convexity in the control of the phase shifters. In this paper, we develop a recursive beam tracking algorithm which can simultaneously achieve fast tracking speed, high tracking accuracy, low complexity, and low pilot overhead. In static scenarios, this algorithm converges to the minimum Cramér-Rao lower bound (CRLB) of beam tracking with high probability. In dynamic scenarios, even at SNRs as low as 0dB, our algorithm is capable of tracking a mobile moving randomly at an absolute angular velocity of 10-20 degrees per second, using only 5 pilot symbols per second. If combining with a simple TDMA pilot pattern, this algorithm can track hundreds of high-speed mobiles in 5G configurations. Our simulations show that the tracking performance of this algorithm is much better than several state-of-the-art algorithms. ‡ Corresponding author.

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Optimal Precoders for Tracking the AoD and AoA of a mmWave Path

Cited by 61 publications

References 46 publications

Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation

Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation

Tracking Position and Orientation Through Millimeter Wave Lens MIMO in 5G Systems

Analog beam tracking in linear antenna arrays: Convergence, optimality, and performance

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