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.

翻译：本文提出了一种通用的联邦学习框架，该框架通过数字通信实现空中计算，并采用一种新的联合信源信道编码方案。该方案无需设备端知晓信道状态信息，利用格码对模型参数进行量化，并利用设备间的干扰。我们设计了一种新颖的服务器端双层接收结构，能够将量化模型参数的整数组合作为格点进行可靠解码，以实现聚合目的。数值实验验证了所提方案的有效性。即使面临信道条件和设备异构性的挑战，所提方案仍显著优于其他空中联邦学习策略。