… technique for building inference models over wireless networks due to … federated learning
with model dissemination), for millimeter-wave (mmWave) aerial-terrestrial integrated networks …

… Abstract—The ever-growing use of unmanned aerial vehicles (UAVs) as aerial users is … ,
namely federated training. Here, the local model updates of federated training and split training …

… The aerial adversaries in the jamming … a federated learning-based on-device jamming
attack detection security architecture for FANET. We enhance the proposed federated learning …

… Abstract—Equipped with machine learning (ML) models, unmanned aerial vehicle (UAV) …
, we propose a federated learning (FL) framework via non-orthogonal multiple access (NOMA) …

To prolong the lifetime of the unmanned aerial vehicles (UAVs), the UAVs need to fulfill their
missions in the shortest possible time. In addition to this requirement, in many applications, …

… architecture to train ML models for supporting advanced applications, like fire tracking and
flood monitoring, in wireless UAV networks. We consider a group of aerial UEs are flying over …

… aerial … A Federated Learning (FL) approach is adopted at the edge to ensure accurate and
up-to-date service provisioning in accordance with the surrounding environment and network …

… Therefore, we propose the use of Unmanned Aerial Vehicles (UAVs) to facilitate the network
in achieving higher communication efficiency in the FL network. The vehicles and the RSUs …

… aerialterrestrial network model where Unmanned Aerial … ) of a Cloud Radio Access Network
(HCRAN) serving different … propose a 2-stage federated learning algorithm among the UEs…

… Federated Learning by Aerial-Assisted Protocol (FLAP) that selects and manages the aerial
link for the federated UEs in each training … % in the number of federated UEs taking part in FL…