UWB WBAN Radio Channels. Effects of the Human Body

Thesis event information

Date and time of the thesis defence

Place of the thesis defence

Lecture room L10

Topic of the dissertation

UWB WBAN Radio Channels. Effects of the Human Body

Doctoral candidate

Licentiate of Science (Technology) Timo Kumpuniemi

Faculty and unit

University of Oulu Graduate School, Faculty of Information Technology and Electrical Engineering, CWC - Networks and systems

Subject of study

Telecommunications Engineering

Opponent

Professor Ben Allen, University of Surrey

Custos

Professor Jari Iinatti, University of Oulu

Add event to calendar

UWB WBAN Radio Channels. Effects of the Human Body

Ultra-wideband (UWB) technology offers several beneficial characteristics suitable, e.g. for short range communications. UWB is specified to have a low transmission power enabling low interference to surrounding systems. It is interference tolerant.

One highly interesting application area for UWB is the usage in wireless body area networks (WBANs). It can be applied, e.g. with human bodies. WBANs enable, e.g. the usage of various type of sensors to measure vital parameters of a human and transmit the data wirelessly to, e.g. medical staff or the medical data gathering centre.

This thesis is based on radio channel measurements by using a vector network ana- lyser together with the data analysis related to the measurements. They are conducted in an anechoic chamber to specially examine the human body effect on radio signals. The results serve, e.g. as a reference to other types of measurements in various surroundings with echoes.

The measurement scenarios consist of on-on, on-off and body- to-body cases with static, pseudo-dynamic and truly dynamic cases. From the results, e.g. path loss models are developed. For channel impulse responses, statistical data fittings are carried out with other results, e.g. tap numbers, cross-correlation values between channels, average fade duration, and level crossing rate.

The results show that no generic model for various scenarios can be derived in order for the models to be accurate. The results depend on several variables, e.g. measurement setup, test person, antenna locations, antennas, data post-processing techniques and type of measurement.
Created 29.11.2025 | Updated 1.12.2025