Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation

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,...

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Main Authors: Macey Ruble, Ismail Guvenc
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
AOA
AOD
Online Access:https://ieeexplore.ieee.org/document/9069939/
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spelling doaj-fa5587d9f8344105a8bc25b5adec5f6c2021-03-30T01:38:32ZengIEEEIEEE Access2169-35362020-01-018755927560610.1109/ACCESS.2020.29884859069939Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter EstimationMacey Ruble0https://orcid.org/0000-0002-3217-6292Ismail Guvenc1Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USADepartment of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USAFifth 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 Tucker form 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 is more computationally efficient than methods such as the canonical polyadic decomposition (CPD) and the Tucker form of the MSVD enables paths to be extracted based on signal energy. The algorithms performance is compared to the CPD method and shown to closely match the Cramer-Rao bound (CRB) of channel parameter estimates through simulations. Additionally, limitations of channel parameter estimation and communication waveform effects are studied.https://ieeexplore.ieee.org/document/9069939/AOAAODchannel estimationMSVDmassive MIMOmmWave
collection DOAJ
language English
format Article
sources DOAJ
author Macey Ruble
Ismail Guvenc
spellingShingle Macey Ruble
Ismail Guvenc
Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation
IEEE Access
AOA
AOD
channel estimation
MSVD
massive MIMO
mmWave
author_facet Macey Ruble
Ismail Guvenc
author_sort Macey Ruble
title Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation
title_short Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation
title_full Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation
title_fullStr Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation
title_full_unstemmed Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation
title_sort multilinear singular value decomposition for millimeter wave channel parameter estimation
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description 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 Tucker form 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 is more computationally efficient than methods such as the canonical polyadic decomposition (CPD) and the Tucker form of the MSVD enables paths to be extracted based on signal energy. The algorithms performance is compared to the CPD method and shown to closely match the Cramer-Rao bound (CRB) of channel parameter estimates through simulations. Additionally, limitations of channel parameter estimation and communication waveform effects are studied.
topic AOA
AOD
channel estimation
MSVD
massive MIMO
mmWave
url https://ieeexplore.ieee.org/document/9069939/
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