Indoor Positioning Based on RSS Fingerprinting in a LTE Network: Method Based on Genetic Algorithms

Lembo, Sergio; Horsmanheimo, Seppo; Honkamaa, Petri

doi:10.1109/iccw.2019.8756883

Cited by 15 publications

(5 citation statements)

References 22 publications

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“…Another good way is to add some RNs in an optimized place so the modules can get enough RSS and work properly and also the final cost is much lower. Consequently, the number and coordinates of RNs should be optimized [19] .…”

Section: System Model and Preliminariesmentioning

confidence: 99%

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A novel relay placement method for smart energy IoT systems in offices with genetic algorithm

Moosavi,

Daryanavard

2023

Comput. Telecommun. Eng.

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<p>Smart energy in large offices and organizations is an important research area of the Internet of Things (IoT). The energy efficiency of buildings is vital for the environment and global sustainability. To achieve satisfactory performance for this goal, WiFi access point (AP) indoor coverage is of high importance. As it costs a lot to add more WiFi to have good coverage in all parts of the office’s buildings, we consider relay node (RN) instead of adding more APs. So in this paper, we propose a novel RN placement in order to improve the indoor coverage of offices considering the signal attenuation using a path-loss model as the main measure for determining positions. The main problem is the placement of these RNs and the required number of them by considering existing APs. At first, we obtain the radio propagation model parameters by considering the data that are collected from the AP. Then based on these parameters, the proposed solution uses a genetic algorithm (GA) for RN placement optimization problem. The experimental results display the effectiveness of the proposed solution for the RN placement problem.</p>

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Section: System Model and Preliminariesmentioning

confidence: 99%

“…There are some references that consider the propagation parameters model, {퐿 , 훾, 휒 } as constant [18,19] . But it is obvious that there are not the same in different places.…”

Section: Effectiveness Of Parameter Learningmentioning

confidence: 99%

A novel relay placement method for smart energy IoT systems in offices with genetic algorithm

Moosavi,

Daryanavard

2023

Comput. Telecommun. Eng.

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“…The proximity approach is a basic method for localization that evaluates the position of a target device concerning a predefined place or region [19], [20]. The proximity locating approach necessitates the deployment of a specified number of detectors at known locations.…”

Section: A Proximity Detection Techniquesmentioning

confidence: 99%

A Comprehensive Review of Indoor/Outdoor Localization Solutions in IoT era: Research Challenges and Future Perspectives

Asaad¹,

Maghdid²

2021

Preprint

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<p>The number of connected mobile devices and Internet of Things (IoT) is growing around us, rapidly. Since, most of the people daily activities are relying on these connected things or devices. Specifically, this past year (with COVID-19) changed daily life in abroad and this is increased the use of IoT enabled technologies in health sector, work, and play. Further, the most common service via using these technologies is the localization/positioning service for different applications including: geo-tagging, billing, contact tracing, health-care system, point-of-interest recommendations, social networking, security, and more. Despite the availability of a large number of localization solutions in the literature, the precision of localization cannot meet the needs of consumers. For that reason, this paper provides an in-depth investigation of the existing technologies and techniques in the localization field, within the IoT era. Furthermore, the benefits and drawbacks of each technique with enabled technologies are illustrated and a comparison between the utilized technologies in the localization is made. The paper as a guideline is also going through all of the metrics that may be used to assess the localization solutions. Finally, the state-of-the-art solutions are examined, with challenges and perspectives regarding indoors/outdoors environments are demonstrated.</p>

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“…In this study, the threshold is set to 1.2 so that it can be applied in common throughout various tests. The proposed technology limits the similarity computation area around the location (x p1 , y p1 ) where the 1 st minima point was detected from the convergence time as in (10) and (11). 10) (11where x s and y s are the correlation computation areas on the database.…”

Section: R (9)mentioning

confidence: 99%

“…Therefore, the fingerprinting method can be more effective than the timing-based localization technology in indoor environments because it is possible to perform localization with a small number of RF signal sources. Lembo et al [11] proposed a neural network (NN) based fingerprinting method to determine a user's location by utilizing instantaneous RSS measurements. Pecoraro et al [12] proposed a localization technology using channel state information (CSI), which is a channel gain per subcarrier, to further improve the performance of the RSS-based fingerprinting method.…”

Section: Introductionmentioning

confidence: 99%

Precise Indoor Localization: Rapidly-Converging 2D Surface Correlation-Based Fingerprinting Technology Using LTE Signal

Lee

Shin

et al. 2020

IEEE Access

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This study proposes a 2D surface correlation-based indoor localization technology using LTE fingerprinting with an accuracy of several meters. The most important problem with RF fingerprinting is that the location discernment of signal strength becomes exceedingly low as the distance from the RF signal source increases. Instantaneous RSS measurement based conventional fingerprinting involves the installation of several signal sources to improve location discernment. However, additional installations of LTE base stations (BSs) are impossible. To improve location discernment, the proposed technology utilizes a spatial RSS pattern extracted using the Pedestrian-Dead Reckoning during user movement. The use of the proposed technology greatly improves the accuracy and availability of LTE signals using the pattern. Additionally, the following two points should be considered. First, the spatially accumulated pattern contains location errors that can cause pattern distortion. The proposed technology performs pattern correction through feature matching using RSS mark and crossroad locations. Second, the accuracy of pattern matching may be decreased prior to sufficient pattern accumulation. For the rapid convergence of the pattern matching, the proposed technology performs correlation pattern analysis. This approach detects the point in which the discernment is increased by pattern accumulation and limits the search range around the matching point. To verify the performance, we conducted tests in a shopping mall where only one LTE BS ID is available. Consequently, the convergence distance of pattern matching was improved by 69% after pattern analysis. Furthermore, it was confirmed that the localization error after convergence improved from 4.16 m to 2.82 m.

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Indoor Positioning Based on RSS Fingerprinting in a LTE Network: Method Based on Genetic Algorithms

Cited by 15 publications

References 22 publications

A novel relay placement method for smart energy IoT systems in offices with genetic algorithm

A novel relay placement method for smart energy IoT systems in offices with genetic algorithm

A Comprehensive Review of Indoor/Outdoor Localization Solutions in IoT era: Research Challenges and Future Perspectives

Precise Indoor Localization: Rapidly-Converging 2D Surface Correlation-Based Fingerprinting Technology Using LTE Signal

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