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

Wenlihan Lu; Ziyi Lu; Jia Yan; Shijian Gao

ICASSP 2025accepted0 citations

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

Wenlihan Lu, Ziyi Lu, Jia Yan, Shijian Gao

Abstract

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.

BibTeX

@inproceedings{icassp2025_sip2netsituation,
  title = {SIP2Net: Situational-Aware Indoor Pathloss-Map Prediction Network for Radio Map Generation},
  author = {Wenlihan Lu and Ziyi Lu and Jia Yan and Shijian Gao},
  booktitle = {ICASSP 2025},
  year = {2025}
}