IGMM-based approach for discovering co-located mobile users

Pedro M. Varela, Jihoon Hong, Tomoaki Ohtsuki

研究成果: Conference contribution


Nowadays people are carrying their mobile devices wherever they go, and as social beings they interact with others all day long. Thus, by exploiting this massive use of smart devices they provide a way to be co-located using only their captured environmental radio signals. In this paper, we design a co-location system that finds groups of people, in real-time, with high accuracy, by exploiting the similarity of their measured radio signals. Our method is based on a nonparametric Bayesian (NPB) method called infinite Gaussian mixture model (IGMM) that allows the model parameters to change with observed input data. This system is designed in a completely centralised manner. Hence, it enables the network to control and manage the formation of the all users' groups. We analyze the performance of our framework, in terms of clustering accuracy, with datasets from a real-world setting to demonstrate its feasibility. We also compare its performance against community detection based clustering method. Results on experiment with real datasets show a better accuracy favoring our approach against its counterpart.

ホスト出版物のタイトル2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
出版ステータスPublished - 2017 2月 2
イベント59th IEEE Global Communications Conference, GLOBECOM 2016 - Washington, United States
継続期間: 2016 12月 42016 12月 8


Other59th IEEE Global Communications Conference, GLOBECOM 2016
国/地域United States

ASJC Scopus subject areas

  • 計算理論と計算数学
  • コンピュータ ネットワークおよび通信
  • ハードウェアとアーキテクチャ
  • 安全性、リスク、信頼性、品質管理


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