Introduces REED as a noncoherent primitive for signed aggregation in OTA-FL using paired resource-element energies, with exact first- and second-moment derivations under Rayleigh fading and a chip-diverse extension.
Optimized power control design for over-the-air federated edge learning
3 Pith papers cite this work. Polarity classification is still indexing.
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An optimal convex-reformulated power control algorithm is derived for signal-level integrated sensing, computing and communication in AirComp-based federated learning under a joint target detection constraint.
Over-the-air federated learning exceeds amplifier peak-power limits in practice, and clipping-filtering mitigation degrades performance especially in multi-carrier OFDM systems.
citing papers explorer
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Resource-Element Energy Difference for Noncoherent Over-the-Air Federated Learning
Introduces REED as a noncoherent primitive for signed aggregation in OTA-FL using paired resource-element energies, with exact first- and second-moment derivations under Rayleigh fading and a chip-diverse extension.
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Analytically Characterized Optimal Power Control for Signal-Level-Integrated Sensing, Computing and Communication in Federated Learning
An optimal convex-reformulated power control algorithm is derived for signal-level integrated sensing, computing and communication in AirComp-based federated learning under a joint target detection constraint.
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On Signal Peak Power Constraint of Over-the-Air Federated Learning
Over-the-air federated learning exceeds amplifier peak-power limits in practice, and clipping-filtering mitigation degrades performance especially in multi-carrier OFDM systems.