Neural Networks for Combinatorial Optimization: a Review of More Than a Decade of Research
INFORMS Journal on Computing
Range-free localization schemes for large scale sensor networks
Proceedings of the 9th annual international conference on Mobile computing and networking
Accuracy characterization for metropolitan-scale Wi-Fi localization
Proceedings of the 3rd international conference on Mobile systems, applications, and services
Fundamentals of wireless communication
Fundamentals of wireless communication
Pervasive and Mobile Computing
Maintaining network connectivity and performance in robot teams: Research Articles
Journal of Field Robotics - Special Issue on Search and Rescue Robots
An efficient approach for trilateration in 3D positioning
Computer Communications
Bluetooth Tracking without Discoverability
LoCA '09 Proceedings of the 4th International Symposium on Location and Context Awareness
Inquiry-Based Bluetooth Indoor Positioning via RSSI Probability Distributions
SPACOMM '10 Proceedings of the 2010 Second International Conference on Advances in Satellite and Space Communications
Place-Its: a study of location-based reminders on mobile phones
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
Practical metropolitan-scale positioning for GSM phones
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Noise-Robust Automatic Speech Recognition Using a Predictive Echo State Network
IEEE Transactions on Audio, Speech, and Language Processing
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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.