A Novel Approach for Inter-User Distance Estimation in 5G mmWave Networks Using Deep Learning

Mondher Bouazizi, Siyuan Yang, Yuwen Cao, Tomoaki Ohtsuki

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

Abstract

Accurate localization of devices in 5G cellular networks is of that utmost importance. This is because location information is a key component of a variety of new emerging applications. In particular, collocation (or co-location) refers to the idea of identifying devices that are located within a certain range from one another. In this paper, we propose a novel technique for inter-user distance estimation that uses low-resolution and high-resolution beam energy-based images as location fingerprints. Our approach uses the beam energy-based images generated by different users to estimate the distance between each pair of them. Nevertheless, we explore the idea of using a deep learning technique referred to as super resolution applied on low-resolution beam energy-based images to enhance their resolution, thus identify collocated users with an accuracy comparable to that of higher resolution ones. More specifically, throughout our experiments, we generate images of resolution 4times 4 and 8times 8 and use these for distance estimation between users. Afterwards, we apply super resolution on images with size 4times 4 to improve their resolution, and compare their results to the ones obtained with the original 8times 8 images. For an area roughly equal to 60times 30 mathrm{m}, our proposed approach reaches an average mean squared error equal to 0.13 m. We also demonstrate how our proposed approach outperforms the conventional ones that rely on user location detection to measure the inter-user distance.

Original languageEnglish
Title of host publicationProceeding - 2021 26th IEEE Asia-Pacific Conference on Communications, APCC 2021
EditorsMohd Fais Mansor, Nordin Ramli, Mahamod Ismail
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages223-228
Number of pages6
ISBN (Electronic)9781728172545
DOIs
Publication statusPublished - 2021
Event26th IEEE Asia-Pacific Conference on Communications, APCC 2021 - Virtual, Kuala Lumpur, Malaysia
Duration: 2021 Oct 112021 Oct 13

Publication series

NameProceeding - 2021 26th IEEE Asia-Pacific Conference on Communications, APCC 2021

Conference

Conference26th IEEE Asia-Pacific Conference on Communications, APCC 2021
Country/TerritoryMalaysia
CityVirtual, Kuala Lumpur
Period21/10/1121/10/13

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Information Systems and Management

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