Bluetooth Low Energy separate-channel fingerprinting with frequency-scanned antennas

A novel Bluetooth Low Energy (BLE) positioning system for IoT devices that employs frequency-scanned leaky-wave antennas (FSLWAs) and the fingerprinting technique is proposed in this work. This system is based on the Received Signal Strength Indicator (RSSI) fingerprinting acquired separately from each one of the three BLE advertising channels. As a main novelty, the Separate-Channel Fingerprinting (SCFP) technique is combined with FSLWAs, specifically tuned to multiplex each BLE advertising channel in a distinct direction. In this way, FSLWAs produce increased spatial resolution in separate-channel radiomaps, which results in greater localization accuracy when compared to the use of conventional monopole antennas installed usually in BLE IoT equipment. This is demonstrated with a practical example involving four BLE beacons distributed in an indoor area of 7 m x 5 m, simulating a practical environment. The proposed system combining SCFP and FSLWAs improves the mean localization error by 39 % compared to conventional monopole antennas without SCFP and 23 % compared to the use of monopoles and SCFP. The system's performance over time and its robustness to the presence of obstacles after calibration are also analyzed, showing the benefits of using SCFP with FSLWAs.

Authors

Institutions

Publication Details

Journal
Internet of Things
Published
2025-08-08
DOI
https://doi.org/10.1016/j.iot.2025.101732
Primary Topic
Bluetooth and Wireless Communication Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bluetooth Low Energy separate-channel fingerprinting with frequency-scanned antennas

José Antonio López-Pastor, Alejandro Gil-Martínez, Astrid Algaba Brazález, José Luis Gómez‐Tornero et al.
Internet of Things
Bluetooth and Wireless Communication Technologies
article

Bluetooth Low Energy separate-channel fingerprinting with frequency-scanned antennas

José Antonio López-Pastor, Alejandro Gil-Martínez, Astrid Algaba Brazález, José Luis Gómez‐Tornero, Antonio Hernández Mateos
article en

Abstract

A novel Bluetooth Low Energy (BLE) positioning system for IoT devices that employs frequency-scanned leaky-wave antennas (FSLWAs) and the fingerprinting technique is proposed in this work. This system is based on the Received Signal Strength Indicator (RSSI) fingerprinting acquired separately from each one of the three BLE advertising channels. As a main novelty, the Separate-Channel Fingerprinting (SCFP) technique is combined with FSLWAs, specifically tuned to multiplex each BLE advertising channel in a distinct direction. In this way, FSLWAs produce increased spatial resolution in separate-channel radiomaps, which results in greater localization accuracy when compared to the use of conventional monopole antennas installed usually in BLE IoT equipment. This is demonstrated with a practical example involving four BLE beacons distributed in an indoor area of 7 m x 5 m, simulating a practical environment. The proposed system combining SCFP and FSLWAs improves the mean localization error by 39 % compared to conventional monopole antennas without SCFP and 23 % compared to the use of monopoles and SCFP. The system's performance over time and its robustness to the presence of obstacles after calibration are also analyzed, showing the benefits of using SCFP with FSLWAs.

Internet of ThingsVol. 33
Universidad Politécnica de Cartagena (ES), Centro Universitario de la Defensa en San Javier (ES)
Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación, European Social Fund
Affordable and clean energy
Openalex Percentile: Top 78%
Bluetooth and Wireless Communication Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.