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Topical Advisory Panel Members’ Collection Series: Wireless Communication Systems
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Topical Advisory Panel Members’ Collection Series: Wireless Communication Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (30 May 2024) | Viewed by 11344

Special Issue Editors

Dr. Qasim Ahmed

E-Mail Website
Guest Editor
Department of Engineering and Technology, School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK
Interests: signal processing; electrical engineering; telecommunications engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Constantinos Angelis

E-Mail Website
Guest Editor
Department of Informatics and Telecommunications, Campus of Arta, University of Ioannina, 47100 Arta, Greece
Interests: wireless sensor networks; wireless telecommunication systems; designs and implementations
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Indoor positioning solutions (IPS) consist of different approaches, frequency bands, and sensor fusion technologies (SFTs). However, they are rigid and inflexible; therefore, it is difficult to demonstrate their different use cases. 6G promises to solve this issue and provides a positioning accuracy of approximately 30 cm. In a well-controlled environment, available context and process information can be employed to improve IPS performance.

This Special Issue is focused on all sensors designed and developed for IPS systems.

Dr. Qasim Ahmed
Dr. Constantinos Angelis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mm-wave systems
  • ultrawide bandwidth (UWB)
  • WiFi
  • BLE
  • received signal strength indicators (RSSI)
  • radio frequency identification (RFID)
  • tera hertz

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Published Papers (3 papers)

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Research

21 pages, 1189 KiB  
Article
Improving Indoor WiFi Localization by Using Machine Learning Techniques
by Hanieh Esmaeili Gorjan and Víctor P. Gil Jiménez
Sensors 2024, 24(19), 6293; https://doi.org/10.3390/s24196293 - 28 Sep 2024
Viewed by 829
Abstract
Accurate and robust positioning has become increasingly essential for emerging applications and services. While GPS (global positioning system) is widely used for outdoor environments, indoor positioning remains a challenging task. This paper presents a novel architecture for indoor positioning, leveraging machine learning techniques [...] Read more.
Accurate and robust positioning has become increasingly essential for emerging applications and services. While GPS (global positioning system) is widely used for outdoor environments, indoor positioning remains a challenging task. This paper presents a novel architecture for indoor positioning, leveraging machine learning techniques and a divide-and-conquer strategy to achieve low error estimates. The proposed method achieves an MAE (mean absolute error) of approximately 1 m for latitude and longitude. Our approach provides a precise and practical solution for indoor positioning. Additionally, some insights on the best machine learning techniques for these tasks are also envisaged. Full article
(This article belongs to the Special Issue Topical Advisory Panel Members’ Collection Series: Wireless Communication Systems)
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22 pages, 2088 KiB  
Article
SALOS—A UWB Single-Anchor Indoor Localization System Based on a Statistical Multipath Propagation Model
by Sven Ole Schmidt, Marco Cimdins, Fabian John and Horst Hellbrück
Sensors 2024, 24(8), 2428; https://doi.org/10.3390/s24082428 - 10 Apr 2024
Cited by 4 | Viewed by 1340
Abstract
Among other methods, UWB-based multi-anchor localization systems have been established for industrial indoor localization systems. However, multi-anchor systems have high costs and installation effort. By exploiting the multipath propagation of the UWB signal, the infrastructure and thus the costs of conventional systems can [...] Read more.
Among other methods, UWB-based multi-anchor localization systems have been established for industrial indoor localization systems. However, multi-anchor systems have high costs and installation effort. By exploiting the multipath propagation of the UWB signal, the infrastructure and thus the costs of conventional systems can be reduced. Our UWB Single-Anchor Localization System (SALOS) successfully pursues this approach. The idea is to create a localization system with sophisticated signal modeling. Therefore, measured reference, like fingerprinting or training, is not required for position estimation. Although SALOS has already been implemented and tested successfully in an outdoor scenario with multipath propagation, it has not yet been evaluated in an indoor environment with challenging and hardly predictable multipath propagation. For this purpose, we have developed new algorithms for the existing hardware, mainly a three-dimensional statistical multipath propagation model for arbitrary spatial geometries. The signal propagation between the anchor and predefined candidate points for the tag position is modeled in path length and complex-valued receive amplitudes. For position estimation, these modeled signals are combined to multiple sets and compared to UWB measurements via a similarity metric. Finally, a majority decision of multiple position estimates is performed. For evaluation, we implement our localization system in a modular fashion and install the system in a building. For a fixed grid of 20 positions, the localization is evaluated in terms of position accuracy. The system results in correct position estimations for more than 73% of the measurements. Full article
(This article belongs to the Special Issue Topical Advisory Panel Members’ Collection Series: Wireless Communication Systems)
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29 pages, 957 KiB  
Article
Indoor Positioning System (IPS) Using Ultra-Wide Bandwidth (UWB)—For Industrial Internet of Things (IIoT)
by Fuhu Che, Qasim Zeeshan Ahmed, Pavlos I. Lazaridis, Pradorn Sureephong and Temitope Alade
Sensors 2023, 23(12), 5710; https://doi.org/10.3390/s23125710 - 19 Jun 2023
Cited by 19 | Viewed by 8575 | Correction
Abstract
The integration of the physical and digital world has become increasingly important, and location-based services have become the most sought-after application in the field of the Internet of Things (IoT). This paper delves into the current research on ultra-wideband (UWB) indoor positioning systems [...] Read more.
The integration of the physical and digital world has become increasingly important, and location-based services have become the most sought-after application in the field of the Internet of Things (IoT). This paper delves into the current research on ultra-wideband (UWB) indoor positioning systems (IPS). It begins by examining the most common wireless communication-based technologies for IPSs followed by a detailed explanation of UWB. Then, it presents an overview of the unique characteristics of UWB technology and the challenges still faced by the IPS implementation. Finally, the paper evaluates the advantages and limitations of using machine learning algorithms for UWB IPS. Full article
(This article belongs to the Special Issue Topical Advisory Panel Members’ Collection Series: Wireless Communication Systems)
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