Bluetooth aided mobile phone localization: A nonlinear neural circuit approach

Shuai Li, Yuesheng Lou, Bo Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

45 Citations (Scopus)


It is meaningful to design a strategy to roughly localize mobile phones without a GPS by exploiting existing conditions and devices especially in environments without GPS availability (e.g., tunnels, subway stations, etc.). The availability of Bluetooth devices for most phones and the existence of a number of GPS equipped phones in a crowd of phone users enable us to design a Bluetooth aided mobile phone localization strategy. With the position of GPS equipped phones as beacons, and with the Bluetooth connection between neighbor phones as proximity constraints, we formulate the problem into an inequality problem defined on the Bluetooth network. A recurrent neural network is developed to solve the problem distributively in real time. The convergence of the neural network and the solution feasibility to the defined problem are both theoretically proven. The hardware implementation architecture of the proposed neural network is also given in this article. As applications, rough localizations of drivers in a tunnel and localization of customers in a supermarket are explored and simulated. Simulations demonstrate the effectiveness of the proposed method.
Original languageEnglish
Article number78
JournalACM Transactions on Embedded Computing Systems
Issue number4
Publication statusPublished - 1 Feb 2014
Externally publishedYes


  • Bluetooth
  • Localization
  • Mobile phone
  • Neural circuit
  • Recurrent neural network

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture


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