Derives explicit discriminant gain as a function of precoding coefficients in ISCC networks and proposes a precoding algorithm that improves sensing accuracy by up to 15% on synthetic data and 10% on real data in low-SNR simulations.
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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.
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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.