RSSI fingerprinting via sparse GPS reference sensors and machine learning achieves 80% location classification accuracy (up to 92% with spaced classes) for UNB IoT devices over a 2.5 km city radius, with multilateration gains when reference density allows.
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Localization in Ultra Narrow Band IoT Networks: Design Guidelines and Trade-Offs
RSSI fingerprinting via sparse GPS reference sensors and machine learning achieves 80% location classification accuracy (up to 92% with spaced classes) for UNB IoT devices over a 2.5 km city radius, with multilateration gains when reference density allows.