Spectrum Allocation and Device Association in Federated Learning-Enabled
Industrial IoT via Hypergraph Matching
Abstract
In this paper, a joint spectrum allocation and device association
problem is investigated for a federated learning aided hierarchical
Industrial Internet of Things (IIoT) system for smart factory. To
achieve the optimization jointly, we design a weighted learning utility
maximization problem, which is a 0-1 integer linear programming problem.
To solve this problem, we convert it into a weighted 3D hypergraph model
by capturing the 3D mapping relation for IIoT device, subchannel, and
edge server. A local search algorithm is then presented to find a 3D
hypergraph matching with maximum total weights as the suboptimal
solution. Simulation results demonstrate the superior performance of the
proposed algorithm compared with the greedy algorithm in the system
learning utility.