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Multimodal Learning for Beamforming Using Camera, LiDAR, and Radio-Frequency Pilots
This paper proposes a multimodal learning framework that integrates camera images, LiDAR point clouds, and radio-frequency (RF) pilots to realize multi-user multiple-input single-output (MU-MISO) beamforming optimization in mixed line-of-sight (LoS) and non-line-of-sight (NLoS) environments. In LoS-
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