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Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements

Gustafsson, F., Gunnarsson, F.·2005·IEEE Signal Processing Magazine

Abstract

Positioning in wireless networks is mainly used for safety, gaming, and commercial services. It is expected to increase in popularity when emergency call services become mandatory as well as with the advent of more advanced location-based services and mobile gaming. In this article, we discuss and illustrate the possibilities and fundamental limitations associated with mobile positioning based on available wireless network measurements. The possibilities include a sensor fusion approach and model-based filtering, while the fundamental limitations provide hard bounds on the accuracy of position estimates, given the information in the measurements in the most favorable situation. The focus of this article is to illustrate the relation between performance requirements, such as those stated by the Federal Communications Commission (FCC), and the available measurements. Specific issues on accuracy limitation in each measurement, such as synchronization and multipath problems, are briefly commented upon. A geometrical example, as well as a realistic example adopted from a cell planning tool, are used for illustration.

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Metadata

Authors
Gustafsson, F., & Gunnarsson, F.
Venue
IEEE Signal Processing Magazine
Published
2005-07
Volume
22
Issue
4
Pages
41-53
ISSN
1053-5888 (ISSN-L)
OpenAlex
W2135401627
Cited by
996
References
0
FWCI
36.23
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements. https://app.cochat.ai/papers/10.1109/msp.2005.1458284
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Gustafsson, F., & Gunnarsson, F. (2005). Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements. IEEE Signal Processing Magazine. https://doi.org/10.1109/msp.2005.1458284

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.