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Non-Coherent Over-the-Air Federated Learning: Protocol, Convergence, and Device Scheduling

Wen, Haifeng et al.
arXiv (All) · Papers
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information-theorymachine-learningsignal-processing
To mitigate the scalability bottleneck in the radio access network (RAN) in federated edge learning (FEEL), over-the-air federated learning (AirFL) exploits waveform superposition over multiple-access channels (MACs) for analog model aggregation. However, coherent AirFL typically relies on stringent
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