… federated learning (FL) algorithms in wireless networks has … of user mobility on the learning
performance. To fill this … hierarchical federated learning (HFL) algorithm in wireless networks …

… network edge, as well as the rising concerns about the data privacy, a new distributed training
framework called federated learning … the model updates via wireless channels. Due to the …

… applications of 5G wireless networks, which shares model parameters through local … a
hierarchical federated learning framework for wireless heterogeneous cellular network (HCN), in …

… machine learning (ML) model aggregation. However, FL over multi-hop wireless networks
has … In this paper, we optimize FL over wireless mesh networks by taking into account the …

… Abstract—In this paper, the convergence time of federated learning (FL), when deployed
over a realistic wireless network, is studied. In particular, with the considered model, wireless …

… delay minimization for federated learning (FL) over wireless communication networks is
investigated. … Since FL involves learning model exchanges between the users and the BS, both …

… in wireless networks with privacy preservation. Federated learning (FL), as a collaborative
learning … , can be leveraged to simultaneously improve learning efficiency and achieve privacy …

… Abstract—Federated Learning (FL) is a distributed learning framework that can deal with
the distributed issue in machine learning and still guarantee high learning performance. …

… We propose a hierarchical federated learning optimization framework over wireless edge
networks to study the problem of participant cost minimization in the worst case. …

… federated learning (FL). To improve the communication efficiency of FL implementations in
wireless … In contrast, this paper studies FL over wireless device-to-device (D2D) networks by …