Mobility-Induced Graph Learning for WiFi Positioning
- RAMO

- 2024년 5월 13일
- 1분 분량
최종 수정일: 2024년 5월 17일
Professor Seong-Lyun Kim's research team, in collaboration with the Korea Railroad Research Institute, has developed a path estimation algorithm using WiFi and a graph neural network. This study transforms user movement patterns into graphs, significantly reducing positioning errors in environments where distance estimation errors are large (2-10m) to about 1m. This result is scheduled to be published in a special issue of the IEEE Journal of Selected Areas in Communications (JSAC), a leading journal in the field of communicationsm with an Impact Factor of 16.4. This work was led by graduate student Kyuwon Han (first author).
K. Han, S.M. Yu, S.-L. Kim, S.-W. Ko "Mobility-Induced Graph Learning for WiFi Positioning," to appear in IEEE Journal on Selected Areas in Communications (JSAC). 2024







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