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On Time-of-Arrival Estimation in NB-IoT Systems

Hu, Sha LU ; Li, Xuhong LU and Rusek, Fredrik LU (2019) In IEEE Wireless Communications and Networking Conference, WCNC 2019-April.
Abstract

We consider time-of-arrival (ToA) estimation for a device working in narrowband Internet-of-Things (NB-IoT) systems. Due to a limited 180 kHz bandwidth, the time-domain auto-correlation function (ACF) of transmitted NB positioning reference signal (NPRS) has a wide main-lobe. Without considering that, the performance of ToA estimation can be degraded for two reasons. Firstly, the NPRS corresponding to different received paths are superimposed on each other under multipath propagation. Secondly, the measured peak-to-average power-ratio (PAPR) for detecting the presence of NPRS is inaccurate. Therefore, in this letter we propose a space-alternating generalized expectation-maximization (SAGE) based method to estimate the number of channel... (More)

We consider time-of-arrival (ToA) estimation for a device working in narrowband Internet-of-Things (NB-IoT) systems. Due to a limited 180 kHz bandwidth, the time-domain auto-correlation function (ACF) of transmitted NB positioning reference signal (NPRS) has a wide main-lobe. Without considering that, the performance of ToA estimation can be degraded for two reasons. Firstly, the NPRS corresponding to different received paths are superimposed on each other under multipath propagation. Secondly, the measured peak-to-average power-ratio (PAPR) for detecting the presence of NPRS is inaccurate. Therefore, in this letter we propose a space-alternating generalized expectation-maximization (SAGE) based method to estimate the number of channel taps, coefficients, and corresponding delays, with taking the imperfect ACF of NPRS into consideration. The proposed ToA estimator only uses time-domain cross-correlations between the received signal and the transmitted NPRS, which yields a low computational-cost. We show through simulations that, it performs close to maximum likelihood (ML) estimator under flat-fading channels, and is superior than traditional estimators under frequency-selective fading channels.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2019 IEEE Wireless Communications and Networking Conference, WCNC 2019
series title
IEEE Wireless Communications and Networking Conference, WCNC
volume
2019-April
article number
8885551
publisher
Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:85074792427
ISSN
1525-3511
ISBN
9781538676462
DOI
10.1109/WCNC.2019.8885551
language
English
LU publication?
yes
id
82c53ca6-a4ee-41e4-bd25-a75d5f421614
date added to LUP
2019-12-02 14:07:30
date last changed
2019-12-03 02:21:17
@inproceedings{82c53ca6-a4ee-41e4-bd25-a75d5f421614,
  abstract     = {<p>We consider time-of-arrival (ToA) estimation for a device working in narrowband Internet-of-Things (NB-IoT) systems. Due to a limited 180 kHz bandwidth, the time-domain auto-correlation function (ACF) of transmitted NB positioning reference signal (NPRS) has a wide main-lobe. Without considering that, the performance of ToA estimation can be degraded for two reasons. Firstly, the NPRS corresponding to different received paths are superimposed on each other under multipath propagation. Secondly, the measured peak-to-average power-ratio (PAPR) for detecting the presence of NPRS is inaccurate. Therefore, in this letter we propose a space-alternating generalized expectation-maximization (SAGE) based method to estimate the number of channel taps, coefficients, and corresponding delays, with taking the imperfect ACF of NPRS into consideration. The proposed ToA estimator only uses time-domain cross-correlations between the received signal and the transmitted NPRS, which yields a low computational-cost. We show through simulations that, it performs close to maximum likelihood (ML) estimator under flat-fading channels, and is superior than traditional estimators under frequency-selective fading channels.</p>},
  author       = {Hu, Sha and Li, Xuhong and Rusek, Fredrik},
  booktitle    = {2019 IEEE Wireless Communications and Networking Conference, WCNC 2019},
  isbn         = {9781538676462},
  issn         = {1525-3511},
  language     = {eng},
  publisher    = {Institute of Electrical and Electronics Engineers Inc.},
  series       = {IEEE Wireless Communications and Networking Conference, WCNC},
  title        = {On Time-of-Arrival Estimation in NB-IoT Systems},
  url          = {http://dx.doi.org/10.1109/WCNC.2019.8885551},
  doi          = {10.1109/WCNC.2019.8885551},
  volume       = {2019-April},
  year         = {2019},
}