Mobile user equipment clustering training method for wireless federated learning

The invention discloses a wireless federated learning-oriented mobile user equipment clustering training method, which is characterized in that an edge service server and a plurality of mobile user equipment are arranged in a wireless network, and each user equipment belongs to a local data set. Firstly, a DBSCAN algorithm and an LEACH algorithm are used to divide users into a plurality of clusters and select cluster heads. Then, each user uses local data to train respective model parameters and uploads the model parameters to a cluster head of a cluster where the user is located for aggregation, and the cluster head further uploads the aggregated model to an edge server for aggregation; and the edge server distributes the aggregated model parameters to the cluster head, and the cluster head further distributes the aggregated model parameters to the user equipment in the cluster for the next round of training. And repeating the steps until convergence. By using the clustering training method, the communicatio