ESN-DAGMM adapts DAGMM with an ESN layer for temporal modeling and reports 269.59% better average clustering quality than baselines on 10% of an O-RAN video-streaming dataset.
Video Streaming Network KPIs for O-RAN Testing,
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Transformer-ESN learns 8D embeddings from O-RAN KPIs that reduce MSE for RSRQ by up to 41.9% and spectral efficiency by 29.9% versus full high-dimensional data in limited-sample regimes.
citing papers explorer
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ESN-DAGMM: A Lightweight Framework for Unsupervised Time-Series Data Monitoring in 5G O-RAN Networks
ESN-DAGMM adapts DAGMM with an ESN layer for temporal modeling and reports 269.59% better average clustering quality than baselines on 10% of an O-RAN video-streaming dataset.
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Learning Low-Dimensional Representation for O-RAN Testing via Transformer-ESN
Transformer-ESN learns 8D embeddings from O-RAN KPIs that reduce MSE for RSRQ by up to 41.9% and spectral efficiency by 29.9% versus full high-dimensional data in limited-sample regimes.