Conventional federated learning (FL) methods face critical challenges in realistic wireless edge networks, where training data are often limited and heterogeneous, which can lead to unstable training and poor generalization. To address these challenges in a principled manner, we propose a novel Bayesian wireless FL framework grounded in Bayesian inference. By explicitly modeling uncertainty, the proposed framework mitigates local overfitting and client drift, thereby enabling more reliable inference. Nevertheless, adopting Bayesian FL increases communication overhead due to the need to transmit richer model information and fundamentally changes the aggregation process beyond simple averaging. To overcome this limitation, we design a dedicated over-the-air computation (AirComp) scheme tailored to Bayesian FL, which efficiently aggregates local posterior distributions at the distribution level by exploiting the superposition property of wireless channels. Simulations validate the proposed framework, demonstrating significant gains in test accuracy over conventional FL methods, particularly in data-scarce and heterogeneous environments.
Jun-Pyo Hong, Hyowoon Seo, Kisong Lee· International Conference on...· 0 citations
Unmanned aerial vehicles (UAVs) have emerged as promising aerial platforms for next-generation wireless networks, offering three-dimensional mobility, rapid deployment, and high line-of-sight (LoS) link probability. This paper presents a structured overview of UAV-assisted wireless communications, covering key network architectures, air-to-ground channel characteristics, mobility-aware deployment and trajectory design, resource management, and multi-UAV cooperation. We further review recent integrations of UAVs with emerging technologies such as artificial intelligence (AI)-driven optimization, reconfigurable intelligent surface (RIS), integrated sensing and communication (ISAC), multiple-input multiple-output (MIMO), and semantic communication. Integration scenarios and recent research trends in beyond-5G and 6G networks are discussed, and open challenges along with future research directions are identified. This survey aims to provide a concise yet comprehensive reference for researchers and engineers working on UAV-assisted wireless network design.
Jueun Jeong, Sehyeon Kwon, Changhui Kim et al.· International Conference on...· 0 citations