Berke KilincBerkay HabibVolkan RodopluHabib, BerkayRodoplu, VolkanKilinc, Berke2025-10-062023979835031161797983503116242769-400310.1109/WF-IoT58464.2023.105394382-s2.0-85195420898https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195420898&doi=10.1109%2FWF-IoT58464.2023.10539438&partnerID=40&md5=aa8f342969a158538fd16ff232f70b30https://gcris.yasar.edu.tr/handle/123456789/8496https://doi.org/10.1109/WF-IoT58464.2023.10539438https://doi.org/10.1109/WF-IOT58464.2023.10539438In this work we propose a novel machine learning-based architecture that processes the Channel Impulse Response (CIR) for mobile Internet of Things (IoT) indoor localization. Our architecture is comprised of three stages: First it pre-processes the Channel Impulse Response of the channel from the mobile device to each anchor by lumping the channel tap values at a configurable resolution. Second the Machine Learning-Based Multipath Profile Processing block applies feature selection to the pre-processed channel taps. Third in the Machine Learning Based Feature Fusion block the selected features are combined to estimate the position of the mobile device. In order to test the performance of our architecture we use two distinct datasets that were collected in home and office environments respectively. The results demonstrate that our work can significantly improve in-door localization accuracy. This work paves the way to significant performance improvements in indoor localization by processing the Channel Impulse Response via machine learning algorithms. © 2024 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessChannel Impulse Response(cir), Indoor Localization, Indoor Positioning, Internet Of Things (iot), Machine Learning (ml), Multipath Profile, Ultra-wideband (uwb), Computer Architecture, Impulse Response, Indoor Positioning Systems, Learning Algorithms, Machine Learning, Ultra-wideband (uwb), Channel Impulse Response, Indoor Localization, Indoor Positioning, Internet Of Thing, Machine-learning, Multipath, Multipath Profile, Ultra-wideband, Ultrawide Band, Internet Of ThingsComputer architecture, Impulse response, Indoor positioning systems, Learning algorithms, Machine learning, Ultra-wideband (UWB), Channel impulse response, Indoor localization, Indoor positioning, Internet of thing, Machine-learning, Multipath, Multipath profile, Ultra-wideband, Ultrawide band, Internet of thingsMultipath ProfileUltra-wideband(uwb)Internet of Things (IoT)Channel Impulse Response(CIR)Indoor LocalizationMachine Learning (ML)Indoor PositioningUltra-Wideband (UWB)Conference Object