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Wireless Communications and Mobile Computing
Volume 2017 (2017), Article ID 4313748, 15 pages
Research Article

In-Body Ranging with Ultra-Wideband Signals: Techniques and Modeling of the Ranging Error

Department of Mechatronics Engineering, Faculty of Engineering, Erciyes University, Melikgazi, 38039 Kayseri, Turkey

Correspondence should be addressed to Muzaffer Kanaan; rt.ude.seyicre@naanakm

Received 19 July 2016; Revised 18 October 2016; Accepted 31 October 2016; Published 15 January 2017

Academic Editor: Mauro Biagi

Copyright © 2017 Muzaffer Kanaan and Memduh Suveren. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.