Federated Learning via Lattice Joint Source-Channel Coding

被引:3
作者
Azimi-Abarghouyi, Seyed Mohammad [1 ]
Varshney, Lay R. [2 ]
机构
[1] KTH Royal Inst Technol, Stockholm, Sweden
[2] Univ Illinois, Urbana, IL USA
来源
2024 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, ISIT 2024 | 2024年
关键词
Federated learning; over-the-air computation; joint source-channel coding; lattice codes; digital communications; COMPUTE-AND-FORWARD; QUANTIZATION; DESIGN;
D O I
10.1109/ISIT57864.2024.10619502
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1623 / 1628
页数:6
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