Time Delay Estimation from Multiband Radio Channel Samples in Nonuniform Noise

Tarik Kazaz; Gerard J.M. Janssen; Alle-Jan van der Veen

doi:10.1109/IEEECONF44664.2019.9049037

Time Delay Estimation from Multiband Radio Channel Samples in Nonuniform Noise

Tarik Kazaz, Gerard J.M. Janssen, Alle-Jan van der Veen

Signal Processing Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Abstract

The multipath radio channel is considered to have a non-bandlimited channel impulse response. Therefore, it is challenging to achieve high resolution time-delay (TD) estimation of multipath components (MPCs) from bandlimited observations of communication signals. It this paper, we consider the problem of multiband channel sampling and TD estimation of MPCs. We assume that the nonideal multi-branch receiver is used for multiband sampling, where the noise is nonuniform across the receiver branches. The resulting data model of Hankel matrices formed from acquired samples has multiple shift-invariance structures, and we propose an algorithm for TD estimation using weighted subspace fitting. The subspace fitting is formulated as a separable nonlinear least squares (NLS) problem, and it is solved using a variable projection method. The proposed algorithm supports high resolution TD estimation from an arbitrary number of bands, and it allows for nonuniform noise across the bands. Numerical simulations show that the algorithm almost attains the Cramér Rao Lower Bound, and it outperforms previously proposed methods such as multiresolution TOA, MI-MUSIC, and ESPRIT.

Original language	English
Title of host publication	2019 53nd Asilomar Conference on Signals, Systems, and Computers
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	1237-1241
Number of pages	5
ISBN (Electronic)	978-1-7281-4300-2
ISBN (Print)	978-1-7281-4301-9
DOIs	https://doi.org/10.1109/IEEECONF44664.2019.9049037
Publication status	Published - 2020
Event	2019 53rd Asilomar Conference on Signals, Systems, and Computers - Pacific Grove, United States Duration: 3 Nov 2019 → 6 Nov 2019 Conference number: 53rd

Conference

Conference	2019 53rd Asilomar Conference on Signals, Systems, and Computers
Country/Territory	United States
City	Pacific Grove
Period	3/11/19 → 6/11/19

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

time-of-arrival
channel estimation
superresolution
sparse recovery
multiband sampling
cognitive radio

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10.1109/IEEECONF44664.2019.9049037

09049037Final published version, 1.28 MB

Cite this

@inproceedings{3f33954e75c74d0b9bdbbecec6f0a51f,

title = "Time Delay Estimation from Multiband Radio Channel Samples in Nonuniform Noise",

abstract = "The multipath radio channel is considered to have a non-bandlimited channel impulse response. Therefore, it is challenging to achieve high resolution time-delay (TD) estimation of multipath components (MPCs) from bandlimited observations of communication signals. It this paper, we consider the problem of multiband channel sampling and TD estimation of MPCs. We assume that the nonideal multi-branch receiver is used for multiband sampling, where the noise is nonuniform across the receiver branches. The resulting data model of Hankel matrices formed from acquired samples has multiple shift-invariance structures, and we propose an algorithm for TD estimation using weighted subspace fitting. The subspace fitting is formulated as a separable nonlinear least squares (NLS) problem, and it is solved using a variable projection method. The proposed algorithm supports high resolution TD estimation from an arbitrary number of bands, and it allows for nonuniform noise across the bands. Numerical simulations show that the algorithm almost attains the Cram{\'e}r Rao Lower Bound, and it outperforms previously proposed methods such as multiresolution TOA, MI-MUSIC, and ESPRIT.",

keywords = "time-of-arrival, channel estimation, superresolution, sparse recovery, multiband sampling, cognitive radio",

author = "Tarik Kazaz and Janssen, {Gerard J.M.} and {van der Veen}, Alle-Jan",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 2019 53rd Asilomar Conference on Signals, Systems, and Computers ; Conference date: 03-11-2019 Through 06-11-2019",

year = "2020",

doi = "10.1109/IEEECONF44664.2019.9049037",

language = "English",

isbn = "978-1-7281-4301-9",

pages = "1237--1241",

booktitle = "2019 53nd Asilomar Conference on Signals, Systems, and Computers",

publisher = "IEEE",

address = "United States",

}

Kazaz, T, Janssen, GJM & van der Veen, A-J 2020, Time Delay Estimation from Multiband Radio Channel Samples in Nonuniform Noise. in 2019 53nd Asilomar Conference on Signals, Systems, and Computers ., 9049037, IEEE, Piscataway, NJ, pp. 1237-1241, 2019 53rd Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, United States, 3/11/19. https://doi.org/10.1109/IEEECONF44664.2019.9049037

Time Delay Estimation from Multiband Radio Channel Samples in Nonuniform Noise. / Kazaz, Tarik; Janssen, Gerard J.M.; van der Veen, Alle-Jan.
2019 53nd Asilomar Conference on Signals, Systems, and Computers . Piscataway, NJ: IEEE, 2020. p. 1237-1241 9049037.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Time Delay Estimation from Multiband Radio Channel Samples in Nonuniform Noise

AU - Kazaz, Tarik

AU - Janssen, Gerard J.M.

AU - van der Veen, Alle-Jan

N1 - Conference code: 53rd

PY - 2020

Y1 - 2020

N2 - The multipath radio channel is considered to have a non-bandlimited channel impulse response. Therefore, it is challenging to achieve high resolution time-delay (TD) estimation of multipath components (MPCs) from bandlimited observations of communication signals. It this paper, we consider the problem of multiband channel sampling and TD estimation of MPCs. We assume that the nonideal multi-branch receiver is used for multiband sampling, where the noise is nonuniform across the receiver branches. The resulting data model of Hankel matrices formed from acquired samples has multiple shift-invariance structures, and we propose an algorithm for TD estimation using weighted subspace fitting. The subspace fitting is formulated as a separable nonlinear least squares (NLS) problem, and it is solved using a variable projection method. The proposed algorithm supports high resolution TD estimation from an arbitrary number of bands, and it allows for nonuniform noise across the bands. Numerical simulations show that the algorithm almost attains the Cramér Rao Lower Bound, and it outperforms previously proposed methods such as multiresolution TOA, MI-MUSIC, and ESPRIT.

AB - The multipath radio channel is considered to have a non-bandlimited channel impulse response. Therefore, it is challenging to achieve high resolution time-delay (TD) estimation of multipath components (MPCs) from bandlimited observations of communication signals. It this paper, we consider the problem of multiband channel sampling and TD estimation of MPCs. We assume that the nonideal multi-branch receiver is used for multiband sampling, where the noise is nonuniform across the receiver branches. The resulting data model of Hankel matrices formed from acquired samples has multiple shift-invariance structures, and we propose an algorithm for TD estimation using weighted subspace fitting. The subspace fitting is formulated as a separable nonlinear least squares (NLS) problem, and it is solved using a variable projection method. The proposed algorithm supports high resolution TD estimation from an arbitrary number of bands, and it allows for nonuniform noise across the bands. Numerical simulations show that the algorithm almost attains the Cramér Rao Lower Bound, and it outperforms previously proposed methods such as multiresolution TOA, MI-MUSIC, and ESPRIT.

KW - time-of-arrival

KW - channel estimation

KW - superresolution

KW - sparse recovery

KW - multiband sampling

KW - cognitive radio

U2 - 10.1109/IEEECONF44664.2019.9049037

DO - 10.1109/IEEECONF44664.2019.9049037

M3 - Conference contribution

SN - 978-1-7281-4301-9

SP - 1237

EP - 1241

BT - 2019 53nd Asilomar Conference on Signals, Systems, and Computers

PB - IEEE

CY - Piscataway, NJ

T2 - 2019 53rd Asilomar Conference on Signals, Systems, and Computers

Y2 - 3 November 2019 through 6 November 2019

ER -

Time Delay Estimation from Multiband Radio Channel Samples in Nonuniform Noise

Abstract

Conference

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Keywords

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