Rethinking Clustered Federated Learning in NOMA Enhanced Wireless Networks

no code implementations • 5 Mar 2024 • Yushen Lin, Kaidi Wang, Zhiguo Ding

This study explores the benefits of integrating the novel clustered federated learning (CFL) approach with non-orthogonal multiple access (NOMA) under non-independent and identically distributed (non-IID) datasets, where multiple devices participate in the aggregation with time limitations and a finite number of sub-channels.

Federated Learning