Dnn-Based Wireless Positioning in an Outdoor Environment

Jin Young Lee, Chahyeon Eom, Youngsu Kwak, Hong Goo Kang, Chungyong Lee

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

5 Citations (Scopus)

Abstract

In this paper, we propose a deep learning based algorithm to estimate the position of an user by utilizing reference signal received power (RSRP) and the location of base stations. To obtain reliable results in a real communication environment, parameters were measured using commercially available base stations and mobile phones within a LTE network. Since the structure of the measured data changes in accordance with the number of connected base stations, it is necessary to work on data uniformity processing before running the deep learning network. Therefore, we extract only the case in which three base stations are connected, using it as a feature of deep learning network. The experimental results reveal that the performance of the proposed algorithm is much better than that of the conventional fingerprint method. The average distance error is reduced from 71.04 meters for the fingerprint-based method to 43.51 meters for the proposed deep learning-based method.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3799-3803
Number of pages5
ISBN (Print)9781538646588
DOIs
Publication statusPublished - 2018 Sep 10
Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Duration: 2018 Apr 152018 Apr 20

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2018-April
ISSN (Print)1520-6149

Conference

Conference2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
Country/TerritoryCanada
CityCalgary
Period18/4/1518/4/20

Bibliographical note

Funding Information:
This work was supported by the ICT R&D program of MSIT/IITP, Republic of Korea. [2017-0-00377-001, AI based wireless network quality monitoring system]

Publisher Copyright:
© 2018 IEEE.

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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