Beamforming-Aided Wireless Multimodal Federated Learning: Dynamic Pruning and Joint Optimization
Wireless multimodal federated learning (MFL) is promising for privacy-preserving edge intelligence, but its practical deployment is challenged by modality heterogeneity, client resource heterogeneity, and the high communication and computation cost of multimodal models. This paper proposes a beamforming-aided wireless...