Client Orchestration and Cost-Efficient Joint Optimization for NOMA-Enabled Hierarchical Federated Learning

no code implementations • 3 Nov 2023 • Bibo Wu, Fang Fang, Xianbin Wang, Donghong Cai, Shu Fu, Zhiguo Ding

Subsequently, given the fuzzy based client-edge association, a joint edge server scheduling and resource allocation problem is formulated.

Federated Learning Problem Decomposition +1

Joint Age-based Client Selection and Resource Allocation for Communication-Efficient Federated Learning over NOMA Networks

no code implementations • 18 Apr 2023 • Bibo Wu, Fang Fang, Xianbin Wang

To address these challenges, in this paper, a joint optimization problem of client selection and resource allocation is formulated, aiming to minimize the total time consumption of each round in FL over a non-orthogonal multiple access (NOMA) enabled wireless network.

Federated Learning