Kumpuniemi T., Mäkelä JP., Hämäläinen M., Iinatti J. (2019) Pseudo-dynamic UWB WBAN Off-Body Radio Channel Measurements – Preliminary Results. In: Mucchi L., Hämäläinen M., Jayousi S., Morosi S. (eds) Body Area Networks: Smart IoT and Big Data for Intelligent Health Management. BODYNETS 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 297. Springer, Cham. https://doi.org/10.1007/978-3-030-34833-5_30
Pseudo-dynamic UWB WBAN off-body radio channel measurements : preliminary results
|Author:||Kumpuniemi, Timo1; Mäkelä, Juha-Pekka1; Hämäläinen, Matti1;|
1Centre for Wireless Communications, University of Oulu, Finland
|Online Access:||PDF Full Text (PDF, 0.5 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019121648425
|Publish Date:|| 2019-12-16
This paper presents measurement results on pseudo-dynamic ultra wideband off-body wireless body area network radio channels. The measurements are performed in an anechoic chamber in a 2–8 GHz frequency band by utilizing a vector network analyzer. A dynamic walking sequence was modeled by a test person who took five different body postures which were each measured statically. As a result, when observed together, the five postures can be used to model a dynamic walking sequence as in a cinema film. The antennas were attached on left and right wrist, and left ankle. The off-body antenna node was set on a pole. The work was repeated for two prototype antenna types: dipole and double loop. The mean attenuations of the first arriving paths were noted to lie between −52… − 68 dB. No large differences were noted between the body postures. The link between left ankle and the pole had the largest attenuation. The averaged channel impulse response durations were noted to lie between eight to nine taps, where one tap corresponds to 0.167 ns in time. The dynamic range on the averaged link types shows values between 17…28 dB. No clear difference was noted in the performance between the antenna types.
Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
|Pages:||394 - 408|
Body Area Networks: Smart IoT and Big Data for Intelligent Health Management. BODYNETS 2019
|Host publication editor:||
EAI International Conference on Body Area Networks
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research has been financially supported in part by Academy of Finland 6Genesis Flagship (grant 318927), and in part by the project WBAN communications in the congested environment (MeCCE).
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019. This is a post-peer-review, pre-copyedit version of an article published in Body Area Networks: Smart IoT and Big Data for Intelligent Health Management. BODYNETS 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 297. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-34833-5_30.