Indoor positioning based on RSS fingerprinting in a LTE Network: Method based on genetic algorithms

S. Lembo; S. Horsmanheimo; P. Honkamaa

doi:10.1109/ICCW.2019.8756883

Indoor positioning based on RSS fingerprinting in a LTE Network: Method based on genetic algorithms

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

11 Citations (Scopus)

Abstract

We study the performance of a composite positioning method based on Genetic Algorithms (GA) for determining the position of an indoor user using Radio Signal Strength (RSS) fingerprinting. RSS samples are obtained from field measurements in a test-bed with a dedicated LTE network. Radio maps are described by functions obtained by symbolic regression. The position of a user is then obtained by solving an optimization problem with the functions and instantaneous measured RSS values. The proposed method is benchmarked against a solution implemented with a Neural Network. Position accuracy is evaluated in scenarios with different characteristics. Conclusions are drawn about performance and complexity of the assessed methods.

Original language	English
Title of host publication	2019 IEEE International Conference on Communications Workshops, ICC Workshops 2019 - Proceedings
Publisher	IEEE Institute of Electrical and Electronic Engineers
Number of pages	6
ISBN (Electronic)	978-1-7281-2373-8
DOIs	https://doi.org/10.1109/ICCW.2019.8756883
Publication status	Published - May 2019
MoE publication type	A4 Article in a conference publication
Event	2019 IEEE International Conference on Communications Workshops: ICC Workshops 2019 - Shanghai, China Duration: 20 May 2019 → 24 May 2019

Workshop

Workshop	2019 IEEE International Conference on Communications Workshops
Country/Territory	China
City	Shanghai
Period	20/05/19 → 24/05/19

Keywords

Genetic Algorithm
Indoor positioning
LTE
Neural Network
RSS fingerprinting
Symbolic Regression

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10.1109/ICCW.2019.8756883

Cite this

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title = "Indoor positioning based on RSS fingerprinting in a LTE Network: Method based on genetic algorithms",

abstract = "We study the performance of a composite positioning method based on Genetic Algorithms (GA) for determining the position of an indoor user using Radio Signal Strength (RSS) fingerprinting. RSS samples are obtained from field measurements in a test-bed with a dedicated LTE network. Radio maps are described by functions obtained by symbolic regression. The position of a user is then obtained by solving an optimization problem with the functions and instantaneous measured RSS values. The proposed method is benchmarked against a solution implemented with a Neural Network. Position accuracy is evaluated in scenarios with different characteristics. Conclusions are drawn about performance and complexity of the assessed methods.",

keywords = "Genetic Algorithm, Indoor positioning, LTE, Neural Network, RSS fingerprinting, Symbolic Regression",

author = "S. Lembo and S. Horsmanheimo and P. Honkamaa",

year = "2019",

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doi = "10.1109/ICCW.2019.8756883",

language = "English",

booktitle = "2019 IEEE International Conference on Communications Workshops, ICC Workshops 2019 - Proceedings",

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note = "2019 IEEE International Conference on Communications Workshops : ICC Workshops 2019 ; Conference date: 20-05-2019 Through 24-05-2019",

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Lembo, S , Horsmanheimo, S & Honkamaa, P 2019, Indoor positioning based on RSS fingerprinting in a LTE Network: Method based on genetic algorithms. in 2019 IEEE International Conference on Communications Workshops, ICC Workshops 2019 - Proceedings., 8756883, IEEE Institute of Electrical and Electronic Engineers, 2019 IEEE International Conference on Communications Workshops, Shanghai, China, 20/05/19. https://doi.org/10.1109/ICCW.2019.8756883

Indoor positioning based on RSS fingerprinting in a LTE Network: Method based on genetic algorithms. / Lembo, S.; Horsmanheimo, S.; Honkamaa, P.
2019 IEEE International Conference on Communications Workshops, ICC Workshops 2019 - Proceedings. IEEE Institute of Electrical and Electronic Engineers, 2019. 8756883.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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N2 - We study the performance of a composite positioning method based on Genetic Algorithms (GA) for determining the position of an indoor user using Radio Signal Strength (RSS) fingerprinting. RSS samples are obtained from field measurements in a test-bed with a dedicated LTE network. Radio maps are described by functions obtained by symbolic regression. The position of a user is then obtained by solving an optimization problem with the functions and instantaneous measured RSS values. The proposed method is benchmarked against a solution implemented with a Neural Network. Position accuracy is evaluated in scenarios with different characteristics. Conclusions are drawn about performance and complexity of the assessed methods.

AB - We study the performance of a composite positioning method based on Genetic Algorithms (GA) for determining the position of an indoor user using Radio Signal Strength (RSS) fingerprinting. RSS samples are obtained from field measurements in a test-bed with a dedicated LTE network. Radio maps are described by functions obtained by symbolic regression. The position of a user is then obtained by solving an optimization problem with the functions and instantaneous measured RSS values. The proposed method is benchmarked against a solution implemented with a Neural Network. Position accuracy is evaluated in scenarios with different characteristics. Conclusions are drawn about performance and complexity of the assessed methods.

KW - Genetic Algorithm

KW - Indoor positioning

KW - LTE

KW - Neural Network

KW - RSS fingerprinting

KW - Symbolic Regression

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PB - IEEE Institute of Electrical and Electronic Engineers

Y2 - 20 May 2019 through 24 May 2019

ER -

Indoor positioning based on RSS fingerprinting in a LTE Network: Method based on genetic algorithms

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Keywords

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