Analysis of Bluetooth Low Energy (BLE) Based Indoor Localization System with Multiple Transmission Power Levels

Qureshi, Umair Mujtaba; Umair, Zuneera; Duan, Yaoxin; Hancke, Gerhard P.

doi:10.1109/isie.2018.8433787

Cited by 16 publications

(6 citation statements)

References 16 publications

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“…In addition to the RSSI-distance relation, the Ground-Truth (GT) position of at least 3 BLE beacons are considered as reference points to estimate the unknown target position. In IPSs based on laterarion, the positioning accuracy mainly depends on the appropriate geometric distribution and position of selected BLE beacons, and on the correctness of the distance estimation [1], [5], [7]. Although in ideal conditions a greater number of BLE beacons can improve the position estimation, in practice, not all of them contribute positively to improving positioning accuracy [13] due to high fluctuations in BLE radio wave propagation signals caused by various noise sources, such as environment geometries, unstable power transmission, NLOS [1].…”

Section: Indoor Positioning Methods Based On Effective Ble Beacon Selection Lateration Ble-rssi Based Ipss Use the Received Signalmentioning

confidence: 99%

A Lateration Method based on Effective Combinatorial Beacon Selection for Bluetooth Low Energy Indoor Positioning

Pascacio

Torres-Sospedra

Casteleyn

2021

2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

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Section: Indoor Positioning Methods Based On Effective Ble Beacon Selection Lateration Ble-rssi Based Ipss Use the Received Signalmentioning

confidence: 99%

A Lateration Method based on Effective Combinatorial Beacon Selection for Bluetooth Low Energy Indoor Positioning

Pascacio

Torres-Sospedra

Casteleyn

2021

2021 17th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

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“…The authors in [13] found that different device orientations can affect the RSS with differences of up to 3 dB at exactly the same TX-RX distance, and that an RSS at 3 m TX-RX distance can be higher (with few dBs) than the RSS at 1 m TX-RX distance, if different receiver orientations are used.…”

Section: B Related Studies On Ble Rss Variabilitymentioning

confidence: 99%

“…RSS measurements from any wireless signal (BLE, Wi-Fi, cellular, etc.) are known to fluctuate due to the presence and movement of people in the signal's path [10], the presence of multipath [11], the switches between carrier frequencies of sub-channels used in the transmitted signal [11], the antenna polarization [12], the orientation of the transmitter (TX) and receiver (RX) [13], [14], and the chipset model [15].…”

Section: Introductionmentioning

confidence: 99%

On the High Fluctuations of Received Signal Strength Measurements With BLE Signals for Contact Tracing and Proximity Detection

et al. 2022

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This paper presents a measurement-based analysis of the Received Signal Strength (RSS) of Bluetooth Low Energy (BLE) signals, under Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) scenarios, performed in tandem at two universities in Tampere, Finland, and Bucharest, Romania. We adopted the same hardware and methodology for measurements in both places, and paid particular attention to the impact of RSS on various environmental factors, such as LOS and NLOS scenarios and interference in 2.4 GHz band. In addition, we considered the receiver orientation and the different frequencies of BLE advertising channels. We show that snapshot RSS measurements typically have high variability, not easily explainable by classical path-loss models. A snapshot recording is defined here as one continuous recording at fixed device locations in a static setup. Our observations also show that aggregated RSS data (i.e., considering several snapshot measurements together) is more informative from a statistical point of view and more in agreement with current theoretical path-loss models than snapshot measurements. However, in BLE applications such as contact tracing and proximity detection, the receivers typically have access only to snapshot measurements (e.g., taken over a short duration of 10-20 minutes or less), so the accuracy of contact-tracing and proximity detection can be highly affected by RSS instabilities. In addition to presenting the measurement-based BLE RSS analysis in a comprehensive and well-documented format, our paper also emphasizes open challenges when BLE RSS is used for contact tracing, ranging, and positioning applications. 3 CH37 CH0 CH1 CH2 CH3 BLE advertising channels BLE data channels 2.4GHz Frequency Band

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“…The works presented in [24,28] motivated us to conduct a comprehensive evaluation of a BLE based WILS by exploring the multiple power transmission feature for target localization in an indoor environment. In [56], we analyzed a BLE based WILS with multiple transmission power levels and used a trilateration algorithm for target localization. We conducted a set of experiments in a classroom environment and estimated the location of the 3 targets in the presence of LOS and NLOS.…”

Section: Related Workmentioning

confidence: 99%

“…Each anchor has the capability to transmit the beacons at multiple transmission power levels [25]. These transmission power levels are listed in [56] and shown in Table 1. The transmission power level is denoted by ρl, where l is the index of the power level as listed in Table 1.…”

Section: Bluetooth Low Energy (Ble) Based Wireless Indoor Localizamentioning

confidence: 99%

Evaluating the Implications of Varying Bluetooth Low Energy (BLE) Transmission Power Levels on Wireless Indoor Localization Accuracy and Precision

Qureshi

Umair

Hancke

2019

Sensors

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Bluetooth Low Energy (BLE) based Wireless Indoor Localization System (WILS) with high localization accuracy and high localization precision is a key requirement in enabling the Internet of Things (IoT) in today’s applications. In this paper, we investigated the effect of BLE signal variations on indoor localization caused by the change in BLE transmission power levels. This issue is not often discussed as most of the works on localization algorithms use the highest power levels but has important practical implications for energy efficiency, e.g., if a designer would like to trade-off localization performance and node lifetime. To analyze the impact, we used the established trilateration based localization model with two methods i.e., Centroid Approximation (CA) and Minimum Mean Square Error (MMSE). We observed that trilateration based localization with MMSE method outperforms the CA method. We further investigated the use of two filters i.e., Low Pass Filter (LPF) and Kalman Filter (KF) and evaluated their effects in terms of mitigating the random variations from BLE signal. In comparison to non-filter based approach, we observed a great improvement in localization accuracy and localization precision with a filter-based approach. Furthermore, in comparison to LPF based trilateration localization with CA, the performance of a KF based trilateration localization with MMSE is far better. An average of 1 m improvement in localization accuracy and approximately 50% improvement in localization precision is observed by using KF in trilateration based localization model with the MMSE method. In conclusion, with KF in trilateration based localization model with MMSE method effectively eliminates random variations in BLE RSS with multiple transmission power levels and thus results in a BLE based WILS with high accuracy and high precision.

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Analysis of Bluetooth Low Energy (BLE) Based Indoor Localization System with Multiple Transmission Power Levels

Cited by 16 publications

References 16 publications

A Lateration Method based on Effective Combinatorial Beacon Selection for Bluetooth Low Energy Indoor Positioning

A Lateration Method based on Effective Combinatorial Beacon Selection for Bluetooth Low Energy Indoor Positioning

On the High Fluctuations of Received Signal Strength Measurements With BLE Signals for Contact Tracing and Proximity Detection

Evaluating the Implications of Varying Bluetooth Low Energy (BLE) Transmission Power Levels on Wireless Indoor Localization Accuracy and Precision

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