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LSTM With Bayesian Loss for Ordinal and Imbalanced Channel Quality Prediction

Accurate prediction of the channel quality indicator (CQI) is crucial for enabling adaptive modulation and coding in next-generation wireless networks. However, CQI prediction remains challenging due to its ordinal nature and the frequent class imbalance observed in real-world datasets. This work pr...

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Bibliografiske detaljer
Principais autores: Virginia Silva, Harold Molina-Bulla, Marcelino Lazaro, Mauricio Rodriguez, Matilde Sanchez-Fernandez
Format: Artigo
Sprog:Inglês
Udgivet: IEEE 2025-01-01
Serier:IEEE Open Journal of the Communications Society
Fag:
Online adgang:https://ieeexplore.ieee.org/document/11196063/
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