Antenna Optimization for WBAN Based on Spherical Wave Functions De-Embedding

TL;DR

This paper introduces a spherical wave function-based modeling approach for WBAN channels, enabling optimized antenna design tailored to dynamic on-body environments, validated through measurements and comparisons.

Contribution

It presents a novel SWF-based channel modeling and antenna de-embedding method for WBANs, facilitating the design of antennas optimized for on-body channels with varying conditions.

Findings

Optimized antenna outperforms standard designs in on-body WBAN scenarios.

SWF modeling accurately captures effects of body pose and anatomy.

Validated through measurements and comparative analysis.

Abstract

Antennas for wireless body area networks (WBAN) need to be modeled with adapted methods because the coupling with the body tissue does not allow for a clear separation between antenna and channel. Especially for dynamically varying on-body channels due to changing body poses, e.g. with head-worn antennas, modeling is challenging and design goals for optimal antennas are difficult to determine. Therefore, in this paper, the modeling of WBAN channels using spherical wave functions (SWF) is utilized for antenna de-embedding and for deriving optimal antenna characteristics that maximize the transmission coefficient for the respective channel. It is evaluated how typical factors influencing WBAN channels (different body anatomies, body postures, and varying positions of the communication nodes), can be modeled statistically with SWF. An optimized antenna design is developed based on the derived optimization method, specifically adapted to the channel of on-body links with eye-wear applications. The results with the optimized antenna are compared to other standard antenna designs and validated against measurements.