Context-aware applications have been gaining huge interest in the last few years. With cell phones becoming ubiquitous computing devices, cell phone localization has become an important research problem. In this paper, we present CellSense, a probabilistic RSSI-based fingerprinting location determination system for GSM phones. We discuss the challenges of implementing a probabilistic fingerprinting localization technique in GSM networks and present the details of the CellSense system and how it addresses the challenges. To evaluate our proposed system, we implemented CellSense on Android-based phones. Results for two different testbeds, representing urban and rural environments, show that CellSense provides at least 23.8% enhancement in accuracy in rural areas and at least 86.4% in urban areas compared to other RSSI-based GSM localization systems. This comes with a minimal increase in computational requirements. We also evaluate the effect of changing the different system parameters on the accuracy-complexity tradeoff.
CellSense: A Probabilistic RSSI-Based GSM Positioning System
Published 2010 in 2010 IEEE Global Telecommunications Conference GLOBECOM 2010
ABSTRACT
PUBLICATION RECORD
- Publication year
2010
- Venue
2010 IEEE Global Telecommunications Conference GLOBECOM 2010
- Publication date
2010-04-19
- Fields of study
Computer Science, Engineering
- Identifiers
- External record
- Source metadata
Semantic Scholar
CITATION MAP
EXTRACTION MAP
CLAIMS
- No claims are published for this paper.
CONCEPTS
- No concepts are published for this paper.
REFERENCES
Showing 1-12 of 12 references · Page 1 of 1
CITED BY
Showing 1-87 of 87 citing papers · Page 1 of 1