SIP2Net: Situational-Aware Indoor Pathloss-Map Prediction Network for Radio Map Generation

This paper presents our indoor pathloss prediction solution to ICASSP 2025 Signal Process Grand Challenge: First Indoor Path Loss Prediction Challenge. The proposed U-Net-based network incorporates dedicated asymmetric convolutions and spatial pyramid pooling to enhance reconstruction quality. Our approach achieves a weighted root mean squared error (RMSE) of 9.411 dB on the final test set, securing the 1st place in the challenge.