Federated Learning via Lattice Joint Source-Channel Coding
Seyed Mohammad Azimi-Abarghouyi Lav R. Varshney
This paper introduces a universal federated learning framework that enables
over-the-air computation via digital communications, using a new joint
source-channel coding scheme. Without relying on channel state information at
devices, this scheme employs lattice codes to both quantize model parameters
and exploit interference from the devices. A novel two-layer receiver structure
at the server is designed to reliably decode an integer combination of the
quantized model parameters as a lattice point for the purpose of aggregation.
Numerical experiments validate the effectiveness of the proposed scheme. Even
with the challenges posed by channel conditions and device heterogeneity, the
proposed scheme markedly surpasses other over-the-air FL strategies.