… Because the multithrow switches are literally the first device after the antenna, they … ing
networks, PAs and LNAs. Figures 4 and 5 show the performance of the Peregrine SP6T antenna …

… often face challenges related to data privacy and bandwidth limitations. Federated Learning
(FL) is an innovative technology that effectively addresses these challenges by leveraging …

… , network components, network structures, main challenges … theory, machine learning, federated
learning and other theories, … satellite鄄aerial 6G networks: state鄄of鄄the鄄art and future …

… to participate in federated learning tasks due to considerable … and hinders the application of
federated learning. In this study, an … their resources in federated learning tasks, where model …

… This paper introduced MEC technology, federated learning … massive and heterogeneous
resources in the network, and builded low-… network, mobile edge computing, federated learning, …

… (CML), a hybrid beamforming and resource allocation optimization method based on
contract theory under hierarchical federated learning (FL) was proposed. First, the system …

… application scenarios such as Internet of Things (IoT), Internet of Vehicles (IoV), Blockchain,
Unmanned Aerial … , DRL),联邦学习(Federated Learning, FL)等,更好的保证计算卸载服务的…

… with an extremely large antenna array and model-based (or model-driven) neural networks.
We also … federated learning can be organically combined with the localization models. …

… localization is a prerequisite for unmanned aerial vehicle (UAV) swarm applications. …
problem and the requirement of high localization accuracy in the UAV application scenario. …

… Recent advances in AI provide many useful tools to handle network optimization problems
with nonconvexity and large scale, which are hard to solve through the traditional methods. …