2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA) 2020
DOI: 10.1109/icmla51294.2020.00083
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Deep Learning-based Symbolic Indoor Positioning using the Serving eNodeB

Abstract: This paper presents a novel indoor positioning method designed for residential apartments. The proposed method makes use of cellular signals emitting from a serving eNodeB which eliminates the need for specialized positioning infrastructure. Additionally, it utilizes Denoising Autoencoders to mitigate the effects of cellular signal loss. We evaluated the proposed method using real-world data collected from two different smartphones inside a representative apartment of eight symbolic spaces. Experimental result… Show more

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Cited by 2 publications
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“…On the other hand, the fourth system is a cellular-based localization system. There are plenty of localization systems that depend on cellular signals for both indoor and outdoor environments [23]- [31]. Fingerprint-based localization systems enjoy several strengths that enable them to yield better performance.…”
Section: Introductionmentioning
confidence: 99%
“…On the other hand, the fourth system is a cellular-based localization system. There are plenty of localization systems that depend on cellular signals for both indoor and outdoor environments [23]- [31]. Fingerprint-based localization systems enjoy several strengths that enable them to yield better performance.…”
Section: Introductionmentioning
confidence: 99%