A closed-form FL convergence upper bound incorporating sensing SNR, dataset size, and transmission reliability enables joint optimization of sensing power, snapshots, and communication power in ISAC systems.
Radar aided 6G beam prediction: Deep learning algorithms and real-world demonstration
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ISAC for AI: A Trade-off Framework Across Data Acquisition and Transfer in Federated Learning
A closed-form FL convergence upper bound incorporating sensing SNR, dataset size, and transmission reliability enables joint optimization of sensing power, snapshots, and communication power in ISAC systems.