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  • 작성자 사진RAMO

Mobility-Induced Graph Learning for WiFi Positioning

최종 수정일: 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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