AI RESEARCH
How Big Should a Wireless Foundation Model Be?
arXiv CS.LG
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ArXi:2605.07266v1 Announce Type: cross Wireless foundation models are rapidly emerging as a key enabler of AI-native communication systems, yet a fundamental question remains unanswered: how large should these models be? We present a principled, physics-grounded answer, showing that the intrinsic dimensionality (dNL, the nonlinear manifold dimension of the channel) acts as the fundamental bottleneck, defining the scaling ceiling once a data-sufficient regime is reached.