AI RESEARCH
A Geometric Algebra-informed NeRF Framework for Generalizable Wireless Channel Prediction
arXiv CS.LG
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ArXi:2604.11983v1 Announce Type: cross In this paper, we propose the geometric algebra-informed neural radiance fields (GAI-NeRF), a novel framework for wireless channel prediction that leverages geometric algebra attention mechanisms to capture ray-object interactions in complex propagation environments. Our approach incorporates global token representations, drawing inspiration from transformer architectures in language and vision domains, to aggregate learned spatial-electromagnetic features and enhance scene understanding.