Practical Metropolitan-Scale Positioning for GSM Phones

By Mike Y. Chen, Timothy Sohn, D. Chmelev, Dirk Hähnel, Jeffrey Hightower, Jeff Hughes, Anthony LaMarca, Fred Potter, I. Smith, Alex Varshavsky. Ubiquitous Computing, 2006

315 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/d58bcabaf25cef951c71fb25fa553ecc960f4702

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Azzedine F. M. Boukerche
2. Deborah Estrin
3. Mani B. Srivastava
4. Antonio Alfredo Ferreira Loureiro
5. Eduardo Freire Nakamura
6. Sunny Consolvo
7. Horácio Oliveira
8. Romit Roy Choudhury

In Transportation

1. Lin Zhong
2. Anthony J. Nicholson
3. Deborah Estrin
4. Horácio Oliveira
5. Romit Roy Choudhury
6. Mani B. Srivastava
7. Azzedine F. M. Boukerche
8. Martin Azizyan

Citations in the corpus

• Context-for-wireless: context-sensitive energy-efficient wireless data transfer (2007, background): “[16] LaMarca, A., Chawathe, Y., Consolvo, S., Hightower, J., Smith, I., Scott, J., Sohn, T., Howard, J., Hughes, J. and Potter, F., Place Lab: Device Positioning Using Radio Beacons in the Wild. in Proc.”
• SurroundSense: mobile phone localization via ambience fingerprinting (2009, background): “Hence, users in adjacent stores can be separated logically, even when their physical positions are ex­tremely close.”
• BreadCrumbs: forecasting mobile connectivity (2008, background): “The same idea has recently been extended to use GSM phone towers rather than WiFi APs [6].”
• Using mobile phones to determine transportation modes (2010, methodology): “Furthermore, using GPS enables the system to obtain granular location information which is useful for our target applications, and not relying on WiFi and GSM features avoids having to create environment specific models to account for network endpoint characteristics in urban, suburban, and rural ar”
• Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning (2009, methodology): “This remote server provides the A-GPS mobile device with satellite orbit and clock information; the initial position and time estimate; satellite selection, range and range date; and position computation.”
• Vehicular Ad Hoc Networks: A New Challenge for Localization-Based Systems (2008, background): “In most cases, the average localization error will be between 90 m and 250 m [30], which is not accurate enough even for VANet applications that do not require accurate and reliable information such as the applications studied in Section 2.”
• MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones (2007, background): “To increase the number of places sampled, we used a GSM­based mobility detection algorithm to target the surveys to mobility transitions.”
• Micro-Blog: sharing and querying content through mobile phones and social participation (2008, background): “Kalman filtering techniques may be particularly applicable in this context [44].”