In-Body Ranging with Ultra-Wideband Signals: Techniques and Modeling of the Ranging Error
Joint Authors
Kanaan, Muzaffer
Suveren, Memduh
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-01-15
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Information Technology and Computer Science
Abstract EN
Results about the problem of accurate ranging within the human body using ultra-wideband signals are shown.
The ability to accurately measure the range between a sensor implanted in the human body and an external receiver can make a number of new medical applications such as better wireless capsule endoscopy, next-generation microrobotic surgery systems, and targeted drug delivery systems possible.
The contributions of this paper are twofold.
First, we propose two novel range estimators: one based on an implementation of the so-called CLEAN algorithm for estimating channel profiles and another based on neural networks.
Second, we develop models to describe the statistics of the ranging error for both types of estimators.
Such models are important for the design and performance analysis of localization systems.
It is shown that the ranging error in both cases follows a heavy-tail distribution known as the Generalized Extreme Value distribution.
Our results also indicate that the estimator based on neural networks outperforms the CLEAN-based estimator, providing ranging errors better than or equal to 3.23 mm with 90% probability.
American Psychological Association (APA)
Kanaan, Muzaffer& Suveren, Memduh. 2017. In-Body Ranging with Ultra-Wideband Signals: Techniques and Modeling of the Ranging Error. Wireless Communications and Mobile Computing،Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1205863
Modern Language Association (MLA)
Kanaan, Muzaffer& Suveren, Memduh. In-Body Ranging with Ultra-Wideband Signals: Techniques and Modeling of the Ranging Error. Wireless Communications and Mobile Computing No. 2017 (2017), pp.1-15.
https://search.emarefa.net/detail/BIM-1205863
American Medical Association (AMA)
Kanaan, Muzaffer& Suveren, Memduh. In-Body Ranging with Ultra-Wideband Signals: Techniques and Modeling of the Ranging Error. Wireless Communications and Mobile Computing. 2017. Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1205863
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1205863