ACCoRD trains an ANN with PPO-Clip reinforcement learning to select conflict resolution actions in O-RAN, reducing negative network events versus rule-based methods in medium and high traffic simulations.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3representative citing papers
Supervised regression models trained on COTS smartphone PHY data predict 5G throughput and BLER across LOS, nLOS, mobility, and multi-user scenarios.
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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ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps
ACCoRD trains an ANN with PPO-Clip reinforcement learning to select conflict resolution actions in O-RAN, reducing negative network events versus rule-based methods in medium and high traffic simulations.
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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.