This book systematically discusses UAV swarm networks from a networking perspective, including adaptive clustering and networking, efficient routing algorithms, and resource scheduling strategies. As shown in Fig. 8.1, we also analyze the opportunities brought by emerging technologies such as distributed learning, semantic communication, and deterministic networks for UAV swarm networks. In Chap. 2 , we propose intelligent clustering and networking methods to address the dynamic topology, unstable links, and self-organization characteristics of UAV swarm networks. By organizing the network efficiently and using optimization algorithms, communication efficiency and network stability are enhanced. Among them, the FSC strategy generates clusters via fission and dynamically adjusts links to improve communication performance. Additionally, to address the limited coverage of UAVs, a RL architecture with centralized training and distributed execution is proposed to solve the problems of “credit allocation” and “false reward signals,” significantly optimizing cooperative communication performance in dynamic environments.