Graph Neural Networks Proposed for Wideband Hybrid Beamforming Optimization in 6G

A new arXiv paper presents an efficient graph neural network method for optimizing multicarrier wideband hybrid beamforming, a key technique for highly directional 6G links. The work targets beam squint, a distortion that grows as 6G systems use much wider frequency bands and that traditionally requires costly true-time-delay filters. The authors position the learning-based approach as a more efficient alternative for next-generation wireless systems.