Floor Detection with Indoor Vertical Positioning in LTE Femtocell Networks

Peral-Rosado, José A. del; Bavaro, Michele; López-Salcedo, José A.; Chawdhry, Pravir; Fortuny-Guasch, J.; Crosta, Paolo; Zanier, Francesca; Crisci, Massimo

doi:10.1109/glocomw.2015.7414170

Cited by 21 publications

(6 citation statements)

References 18 publications

(17 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the indoor environment, the antennas of BSs are usually deployed under the ceiling and have same height, which lead to a high vertical dilution of precision and makes the system cannot provide reliable vertical positioning results [ 25 ]. Therefore, the vertical positioning results are usually provided by other sensors [ 26 ]. Therefore, only the horizontal positioning is considered in this paper.…”

Section: Gdop For the Hybrid Tdoa/rtt/doa Positioningmentioning

confidence: 99%

Base Station Selection for Hybrid TDOA/RTT/DOA Positioning in Mixed LOS/NLOS Environment

Deng

Wang

Zheng

et al. 2020

Sensors

View full text Add to dashboard Cite

The fifth generation (5G) cellular communication system is designed to support Time Difference of Arrival (TDOA), Round-Trip Time (RTT), and Direction of Arrival (DOA) measurements for indoor positioning. To mitigate the positioning error caused by non-line-of-sight (NLOS), existing base station selection methods identify channel conditions and only use line-of-sight (LOS) signals for positioning. However, different selected base station combination would lead to a different geometric dilution of precision (GDOP), base station selection based only on channel condition is not fully applicable for the hybrid positioning. This paper derives the GDOP for the hybrid TDOA, RTT, and DOA positioning, and proposes a GDOP-assisted base station selection method, which is based on both channel conditions and GDOP value changes. The simulation shows that using the proposed base station selection method could lead to higher positioning accuracy than base station selection based only on channel condition. In the simulation, in the side region of the scenario, where the change of selected base station combination causes a notable increment in GDOP value, the positioning accuracy improvement caused by the proposed method is greater than that in the center region.

show abstract

Section: Gdop For the Hybrid Tdoa/rtt/doa Positioningmentioning

confidence: 99%

Base Station Selection for Hybrid TDOA/RTT/DOA Positioning in Mixed LOS/NLOS Environment

Deng

Wang

Zheng

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…The ANTs are deployed at the ceiling with same height, high vertical dilution of precision makes the system cannot provide reliable vertical positioning results [29], which is usually obtained by other sensors [30].…”

Section: System Modelmentioning

confidence: 99%

A Closed-Form Localization Algorithm and GDOP Analysis for Multiple TDOAs and Single TOA Based Hybrid Positioning

et al. 2019

View full text Add to dashboard Cite

Cellular communication systems support mobile phones positioning function for Enhanced-911 (E-911) location requirements, but the positioning accuracy is poor. The fifth-generation (5G) cellular communication system can use indoor distribution systems to provide accurate multiple time-difference-of-arrival (TDOA) and single time-of-arrival (TOA) measurements, which could significantly improve the indoor positioning ability. Unlike iterative localization algorithms for TDOA or TOA, the existing closed-form algorithms, such as the Chan-Ho algorithm, do not have convergence problems, but can only estimate position based on one kind of measurement. This paper proposes a closed-form localization algorithm for multiple TDOAs and single TOA measurements. The proposed algorithm estimates the final position result using three-step weighted least squares (WLSs). The first WLS provides an initial position for the last two steps. Then the algorithm uses two WLSs to estimate position based on heteroscedastic TDOA and TOA measurements. In addition, the geometric dilution of precision (GDOP) of the proposed hybrid TDOA and TOA positioning has been derived. The analysis of GDOP shows that the proposed hybrid positioning has lower GDOP than TDOA-only positioning, which means the proposed hybrid positioning has a higher accuracy limitation than TDOA-only positioning. The simulation shows that the proposed localization algorithm could have better performance than closed-form TDOA-only positioning methods, and the positioning accuracy could approximate Cramer-Rao lower bound (CRLB) when the TDOA measurement errors are small.

show abstract

“…Therefore, floors with an uneven structure and open spaces can cause high identification errors [14]. Floor detection using the cellular networks data has also been done in [15]. Floor detection, also termed vertical positioning, is calculated using the femtocells placed in the experiment area.…”

Section: Introductionmentioning

confidence: 99%

Floor Identification Using Magnetic Field Data with Smartphone Sensors

Ashraf

Hur

Shafiq

et al. 2019

Sensors

View full text Add to dashboard Cite

Floor identification plays a key role in multi-story indoor positioning and localization systems. Current floor identification systems rely primarily on Wi-Fi signals and barometric pressure data. Barometric systems require installation of additional standalone sensors to perform floor identification. Wi-Fi systems, on the other hand, are vulnerable to the dynamic environment and adverse effects of path loss, shadowing, and multipath fading. In this paper, we take advantage of a pervasive magnetic field to compensate for the limitations of these systems. We employ smartphone sensors to make the proposed scheme infrastructure free and cost-effective. We use smartphone magnetic sensors to identify the floors in a multi-story building with improved accuracy. Floor identification is performed with user activities of normal walking, call listening, and phone swinging. Various machine learning techniques are leveraged to identify user activities. Extensive experiments are performed to evaluate the proposed magnetic-data-based floor identification scheme. Additionally, the impact of device heterogeneity on floor identification is investigated using Samsung Galaxy S8, LG G6, and LG G7 smartphones. Research results demonstrate that the magnetic floor identification outperforms barometric and Wi-Fi-enabled floor detection techniques. A floor change module is incorporated to further enhance the accuracy of floor identification.

show abstract

Floor Detection with Indoor Vertical Positioning in LTE Femtocell Networks

Cited by 21 publications

References 18 publications

Base Station Selection for Hybrid TDOA/RTT/DOA Positioning in Mixed LOS/NLOS Environment

Base Station Selection for Hybrid TDOA/RTT/DOA Positioning in Mixed LOS/NLOS Environment

A Closed-Form Localization Algorithm and GDOP Analysis for Multiple TDOAs and Single TOA Based Hybrid Positioning

Floor Identification Using Magnetic Field Data with Smartphone Sensors

Contact Info

Product

Resources

About