Localization of Internet of Things network via Euclidean distance matrix completion

Luong Nguyen, Byonghyo Shim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a matrix completion algorithm to acquire the sensor map of Internet of Things (IoT) network. Our approach consists of two main steps to reconstruct Euclidean distance matrix. Firstly, we formulate the Euclidean distance matrix completion problem as an unconstrained optimization in smooth Riemannian manifold. We next employ nonlinear conjugate gradient algorithm on this manifold to solve the matrix completion problem. From the numerical experiments, we show that the proposed algorithm is effective recovering the distance matrix accurately with much smaller measurement than that required by conventional approaches and also outperforms the state-of-the-art matrix completion algorithms both in noise and noiseless scenarios.

Original languageEnglish
Title of host publication2016 IEEE/CIC International Conference on Communications in China, ICCC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509021437
DOIs
Publication statusPublished - 2016 Oct 21
Externally publishedYes
Event2016 IEEE/CIC International Conference on Communications in China, ICCC 2016 - Chengdu, China
Duration: 2016 Jul 272016 Jul 29

Other

Other2016 IEEE/CIC International Conference on Communications in China, ICCC 2016
CountryChina
CityChengdu
Period16/7/2716/7/29

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

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  • Cite this

    Nguyen, L., & Shim, B. (2016). Localization of Internet of Things network via Euclidean distance matrix completion. In 2016 IEEE/CIC International Conference on Communications in China, ICCC 2016 [7636902] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCChina.2016.7636902