The University of Southampton
University of Southampton Institutional Repository

Quantum-assisted indoor localization for uplink mm-wave and downlink visible light communication systems

Quantum-assisted indoor localization for uplink mm-wave and downlink visible light communication systems
Quantum-assisted indoor localization for uplink mm-wave and downlink visible light communication systems
With the proliferation of millimeter-Wave (mm-Wave) systems and visible light communications (VLCs), indoor localization may find multiple applications. When high localization accuracy is required and triangulation is not possible due to the infrastructure and scenario limitations, the computational complexity of searching on a virtual grid may become excessive. In this paper, we amalgamate uplink mm-Wave-based and downlink VLC-based localization. We employ quantum search algorithms for reducing the computational complexity required for achieving the optimal full-search-based performance. Regarding the uplink mm-Wave-based localization, we employ a single anchor equipped with multiple antenna elements and we exploit the specular multipath components created by the room’s walls. The proposed solutions outperform the state-of-the-art algorithms. Furthermore, various channel models are considered based on real indoors mm-Wave measurements. By using the VLC-based triangulation for downlink and the proposed mm-Wave-based localization algorithm for uplink, there was an average positioning error of 5.6 cm in the room considered, while requiring 261 database queries on average.
Computational complexity, Dürr-Høyer algorithm, fingerprinting, Grover’s quantum search algorithm, localization, mm-Wave, quantum computing, visible light communications
2169-3536
23327-23351
Botsinis, Panagiotis
d7927fb0-95ca-4969-9f8c-1c0455524a1f
Alanis, Dimitrios
8ae8ead6-3974-4886-8e17-1b4bff1d94e0
Feng, Simeng
038a3c0d-9d57-4031-8d38-2203ea230e79
Babar, Zunaira
23ede793-1796-449d-b5aa-93a297e5677a
Nguyen, Hung
6f5a71ef-ea98-49e0-9be7-7f5bb9880f52
Chandra, Daryus
d629163f-25d0-42fd-a912-b35cd93e8334
Ng, Soon Xin
e19a63b0-0f12-4591-ab5f-554820d5f78c
Zhang, Rong
3be8f78f-f079-4a3f-a151-76ecd5f378f4
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Botsinis, Panagiotis
d7927fb0-95ca-4969-9f8c-1c0455524a1f
Alanis, Dimitrios
8ae8ead6-3974-4886-8e17-1b4bff1d94e0
Feng, Simeng
038a3c0d-9d57-4031-8d38-2203ea230e79
Babar, Zunaira
23ede793-1796-449d-b5aa-93a297e5677a
Nguyen, Hung
6f5a71ef-ea98-49e0-9be7-7f5bb9880f52
Chandra, Daryus
d629163f-25d0-42fd-a912-b35cd93e8334
Ng, Soon Xin
e19a63b0-0f12-4591-ab5f-554820d5f78c
Zhang, Rong
3be8f78f-f079-4a3f-a151-76ecd5f378f4
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Botsinis, Panagiotis, Alanis, Dimitrios, Feng, Simeng, Babar, Zunaira, Nguyen, Hung, Chandra, Daryus, Ng, Soon Xin, Zhang, Rong and Hanzo, Lajos (2017) Quantum-assisted indoor localization for uplink mm-wave and downlink visible light communication systems. IEEE Access, 5 (1), 23327-23351. (doi:10.1109/ACCESS.2017.2733557).

Record type: Article

Abstract

With the proliferation of millimeter-Wave (mm-Wave) systems and visible light communications (VLCs), indoor localization may find multiple applications. When high localization accuracy is required and triangulation is not possible due to the infrastructure and scenario limitations, the computational complexity of searching on a virtual grid may become excessive. In this paper, we amalgamate uplink mm-Wave-based and downlink VLC-based localization. We employ quantum search algorithms for reducing the computational complexity required for achieving the optimal full-search-based performance. Regarding the uplink mm-Wave-based localization, we employ a single anchor equipped with multiple antenna elements and we exploit the specular multipath components created by the room’s walls. The proposed solutions outperform the state-of-the-art algorithms. Furthermore, various channel models are considered based on real indoors mm-Wave measurements. By using the VLC-based triangulation for downlink and the proposed mm-Wave-based localization algorithm for uplink, there was an average positioning error of 5.6 cm in the room considered, while requiring 261 database queries on average.

Text
07997701 - Accepted Manuscript
Available under License Creative Commons Attribution.
Download (5MB)
Text
access-hanzo-2733557-proof - Proof
Restricted to Repository staff only
Request a copy

More information

Accepted/In Press date: 26 July 2017
e-pub ahead of print date: 31 July 2017
Keywords: Computational complexity, Dürr-Høyer algorithm, fingerprinting, Grover’s quantum search algorithm, localization, mm-Wave, quantum computing, visible light communications

Identifiers

Local EPrints ID: 413031
URI: http://eprints.soton.ac.uk/id/eprint/413031
ISSN: 2169-3536
PURE UUID: 1a070f84-180f-4a31-b991-14f4eebeeb56
ORCID for Dimitrios Alanis: ORCID iD orcid.org/0000-0002-6654-1702
ORCID for Zunaira Babar: ORCID iD orcid.org/0000-0002-7498-4474
ORCID for Hung Nguyen: ORCID iD orcid.org/0000-0001-6349-1044
ORCID for Daryus Chandra: ORCID iD orcid.org/0000-0003-2406-7229
ORCID for Soon Xin Ng: ORCID iD orcid.org/0000-0002-0930-7194
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 14 Aug 2017 16:30
Last modified: 18 Mar 2024 04:01

Export record

Altmetrics

Contributors

Author: Panagiotis Botsinis
Author: Dimitrios Alanis ORCID iD
Author: Simeng Feng
Author: Zunaira Babar ORCID iD
Author: Hung Nguyen ORCID iD
Author: Daryus Chandra ORCID iD
Author: Soon Xin Ng ORCID iD
Author: Rong Zhang
Author: Lajos Hanzo ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×