FOMRadio: Nonstationary Operator Flow Matching for Radio Map Generation

Generating radio maps from scene geometry and transmitter configurations requires combining long-range propagation with local, scene-dependent interactions. We propose FOMradio, a conditional flow-matching model with a geometry-conditioned nonstationary Fourier operator. Its velocity network couples distant locations spectrally, while an amplitude–phase gate and a residual spatial branch adapt the retained modes and recover structures beyond them. A condition encoder integrates building heights, analytical physical parameters, and transmitter configurations, making the effective kernel. \method transports a multiscale Gaussian random-field source along a straight conditional path, separating spatially structured uncertainty from environment-dependent transport without access to the target radio map at inference. Experiments on RadioMapSeer and U6G demonstrate improved pixelwise accuracy across static and dynamic scenario and variations in cross-configurations, cross-frequency bands, and beam direction.