Supervised regression models trained on COTS smartphone PHY data predict 5G throughput and BLER across LOS, nLOS, mobility, and multi-user scenarios.
Alves, Joao Guilherme A
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cs.NI 2years
2026 2representative citing papers
Supervised ML models trained on smartphone-captured 5G metrics can predict uplink throughput and block error rate across indoor/outdoor and mobility scenarios.
citing papers explorer
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ML-Based Real-Time Downlink Performance Prediction in Standalone 5G NR Using Smartphones
Supervised regression models trained on COTS smartphone PHY data predict 5G throughput and BLER across LOS, nLOS, mobility, and multi-user scenarios.
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ML and Smartphones Assisted Real-Time Uplink Performance Prediction in 5G Cellular System
Supervised ML models trained on smartphone-captured 5G metrics can predict uplink throughput and block error rate across indoor/outdoor and mobility scenarios.