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<dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:invenio="http://invenio-software.org/elements/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>doi:10.1109/JIOT.2026.3666747</dc:identifier><dc:language>eng</dc:language><dc:creator>Losada, M. A.</dc:creator><dc:creator>Carro Ceballos, P. L.</dc:creator><dc:creator>López, A.</dc:creator><dc:creator>García-Dúcar, P.</dc:creator><dc:creator>Mingo Sanz, J. de</dc:creator><dc:creator>Valdovinos, A.</dc:creator><dc:title>Highly linear ioT-over-plastic optical fiber transmission with low complexity cluster-based predistortion.</dc:title><dc:identifier>ART-2026-148428</dc:identifier><dc:description>In the context of ultra-low end applications such as smart homes, smart vehicles and Industrial Internet of Things (IIoT), the use of Plastic Optical Fibers (POFs) as communications backbone to enable the convergence of wireless and optical systems has emerged as a cost-effective and ruggedized solution. The transmission of standalone Narrowband IoT (NB-IoT) signals through large-core Step-Index POF (SI-POF) can be achieved by directly modulating a laser diode at the cost of introducing non-linear effects. In this work, the performance of a Radio-over-POF (RoPOF) link is enhanced by Digital Predistortion (DPD) using a memoryless polynomial approach whose complexity is reduced by scaling down the number of samples using a novel technique that preserves the data statistics by organizing the data into a number of clusters.</dc:description><dc:date>2026</dc:date><dc:source>http://zaguan.unizar.es/record/169900</dc:source><dc:doi>10.1109/JIOT.2026.3666747</dc:doi><dc:identifier>http://zaguan.unizar.es/record/169900</dc:identifier><dc:identifier>oai:zaguan.unizar.es:169900</dc:identifier><dc:relation>info:eu-repo/grantAgreement/ES/AEI/PID2021-122505OB-C33</dc:relation><dc:relation>info:eu-repo/grantAgreement/ES/DGA-FSE/T20-23R</dc:relation><dc:relation>info:eu-repo/grantAgreement/ES/DGA/T31-23R</dc:relation><dc:identifier.citation>IEEE INTERNET OF THINGS JOURNAL (2026), [12 pp.]</dc:identifier.citation><dc:rights>by</dc:rights><dc:rights>https://creativecommons.org/licenses/by/4.0/deed.es</dc:rights><dc:rights>info:eu-repo/semantics/openAccess</dc:rights></dc:dc>

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