Reproduce “Transforming Indoor Localization: Advanced Transformer Architecture for NLOS Dominated Wireless Environments with Distributed Sensors” on OpenResearch

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About this paper

Saad Masrur, Jung-Fu, Cheng, Atieh R. Khamesi, Ismail Guvenc

The paper presents sensor-snapshot tokenization (SST) for Transformer-based indoor positioning from power delay profiles (PDPs), giving each sensor’s delay history its own token so attention can compare sensors. In a simulated obstructed factory, SST reaches a 90th-percentile 2D error of 0.388 m, versus 0.6598 m with patch tokens. This result is simulation-bound.

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