A multi-server wireless federated learning scheme combining secret sharing and artificial noise alignment achieves communication latency within a factor of 4 of the information-theoretic optimum, and is asymptotically optimal when servers far outnumber users.
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Asymptotically Optimal Secure Aggregation for Wireless Federated Learning with Multiple Servers
A multi-server wireless federated learning scheme combining secret sharing and artificial noise alignment achieves communication latency within a factor of 4 of the information-theoretic optimum, and is asymptotically optimal when servers far outnumber users.