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AI-RAN

topic1 events
papersSEP 10 04:00 UTC

Predicting HARQ Retransmissions to Improve MCS Selection in 5G AI-RAN

Researchers tackle a weakness in 5G link adaptation, where modulation and coding scheme choices depend on channel measurements and HARQ feedback that quickly become outdated in fast-changing conditions. Their data-driven approach predicts the likelihood of retransmissions, allowing the network to select more robust transmission parameters proactively. The work targets AI-enhanced radio access networks, where such predictions could improve throughput and reliability.

5g/wireless/machine-learning/research