Localization in Internet of Things network: Matrix completion approach

Luong Nguyen; Sangtae Kim; Byonghyo Shim

doi:10.1109/ITA.2016.7888154

Localization in Internet of Things network: Matrix completion approach

Luong Nguyen
, Sangtae Kim
, Byonghyo Shim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

15 Citations (Scopus)

Abstract

In this paper, we propose a matrix completion algorithm for Internet of Things (IoT) localization. In the proposed algorithm, we recast Euclidean distance matrix completion problem as an unconstrained optimization in smooth Riemannian manifold and then propose a nonlinear conjugate gradient method on this manifold to reconstruct Euclidean distance matrix. The empirical results show that the proposed algorithm is effective and also outperforms state-of-the-art matrix completion algorithms both in noise and noiseless scenarios.

Original language	English
Title of host publication	2016 Information Theory and Applications Workshop, ITA 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509025299
DOIs	https://doi.org/10.1109/ITA.2016.7888154
Publication status	Published - 2017 Mar 27
Externally published	Yes
Event	2016 Information Theory and Applications Workshop, ITA 2016 - La Jolla, United States Duration: 2016 Jan 31 → 2016 Feb 5

Publication series

Name	2016 Information Theory and Applications Workshop, ITA 2016

Other

Other	2016 Information Theory and Applications Workshop, ITA 2016
Country/Territory	United States
City	La Jolla
Period	16/1/31 → 16/2/5

Bibliographical note

Funding Information:
This work was partly supported by the Brain Korea 21 Plus Project in 2015, the ICT R&D program of MSIP/IITP [B0126-15-1017, Spectrum Sensing and Future Radio Communication Platforms] and the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (2014R1A5A1011478).

Publisher Copyright:
© 2016 IEEE.

ASJC Scopus subject areas

Computer Networks and Communications
Computer Science Applications
Artificial Intelligence
Information Systems
Signal Processing

Access to Document

10.1109/ITA.2016.7888154

Cite this

Localization in Internet of Things network: Matrix completion approach. / Nguyen, Luong; Kim, Sangtae; Shim, Byonghyo.
2016 Information Theory and Applications Workshop, ITA 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7888154 (2016 Information Theory and Applications Workshop, ITA 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Nguyen, L, Kim, S & Shim, B 2017, Localization in Internet of Things network: Matrix completion approach. in 2016 Information Theory and Applications Workshop, ITA 2016., 7888154, 2016 Information Theory and Applications Workshop, ITA 2016, Institute of Electrical and Electronics Engineers Inc., 2016 Information Theory and Applications Workshop, ITA 2016, La Jolla, United States, 16/1/31. https://doi.org/10.1109/ITA.2016.7888154

@inproceedings{3a3d71fd6c5940629480a501e4d9fd22,

title = "Localization in Internet of Things network: Matrix completion approach",

abstract = "In this paper, we propose a matrix completion algorithm for Internet of Things (IoT) localization. In the proposed algorithm, we recast Euclidean distance matrix completion problem as an unconstrained optimization in smooth Riemannian manifold and then propose a nonlinear conjugate gradient method on this manifold to reconstruct Euclidean distance matrix. The empirical results show that the proposed algorithm is effective and also outperforms state-of-the-art matrix completion algorithms both in noise and noiseless scenarios.",

author = "Luong Nguyen and Sangtae Kim and Byonghyo Shim",

note = "Funding Information: This work was partly supported by the Brain Korea 21 Plus Project in 2015, the ICT R\&D program of MSIP/IITP [B0126-15-1017, Spectrum Sensing and Future Radio Communication Platforms] and the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (2014R1A5A1011478). Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 Information Theory and Applications Workshop, ITA 2016 ; Conference date: 31-01-2016 Through 05-02-2016",

year = "2017",

month = mar,

day = "27",

doi = "10.1109/ITA.2016.7888154",

language = "English",

series = "2016 Information Theory and Applications Workshop, ITA 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2016 Information Theory and Applications Workshop, ITA 2016",

}

TY - GEN

T1 - Localization in Internet of Things network

T2 - 2016 Information Theory and Applications Workshop, ITA 2016

AU - Nguyen, Luong

AU - Kim, Sangtae

AU - Shim, Byonghyo

N1 - Funding Information: This work was partly supported by the Brain Korea 21 Plus Project in 2015, the ICT R&D program of MSIP/IITP [B0126-15-1017, Spectrum Sensing and Future Radio Communication Platforms] and the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (2014R1A5A1011478). Publisher Copyright: © 2016 IEEE.

PY - 2017/3/27

Y1 - 2017/3/27

N2 - In this paper, we propose a matrix completion algorithm for Internet of Things (IoT) localization. In the proposed algorithm, we recast Euclidean distance matrix completion problem as an unconstrained optimization in smooth Riemannian manifold and then propose a nonlinear conjugate gradient method on this manifold to reconstruct Euclidean distance matrix. The empirical results show that the proposed algorithm is effective and also outperforms state-of-the-art matrix completion algorithms both in noise and noiseless scenarios.

AB - In this paper, we propose a matrix completion algorithm for Internet of Things (IoT) localization. In the proposed algorithm, we recast Euclidean distance matrix completion problem as an unconstrained optimization in smooth Riemannian manifold and then propose a nonlinear conjugate gradient method on this manifold to reconstruct Euclidean distance matrix. The empirical results show that the proposed algorithm is effective and also outperforms state-of-the-art matrix completion algorithms both in noise and noiseless scenarios.

UR - https://www.scopus.com/pages/publications/85018302834

U2 - 10.1109/ITA.2016.7888154

DO - 10.1109/ITA.2016.7888154

M3 - Conference contribution

AN - SCOPUS:85018302834

T3 - 2016 Information Theory and Applications Workshop, ITA 2016

BT - 2016 Information Theory and Applications Workshop, ITA 2016

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 31 January 2016 through 5 February 2016

ER -

Localization in Internet of Things network: Matrix completion approach

Abstract

Publication series

Other

Bibliographical note

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this