Abstract-A compact wearable antenna system, completely made out of textile materials for integration into protective garments, is proposed. The system implements combined pattern and polarization diversity to improve the quality of the communication link. The performance of the on-body antenna system, integrated into a firefighter jacket worn by a test person, was investigated in an indoor measurement campaign. Several receiver diversity schemes and different combining techniques were evaluated in terms of bit error rate, signal-to-noise ratio and signal correlations. By comparing them to theoretical results, we demonstrate the reliability of the proposed system and the advantage of using diversity.
A novel manufacturing procedure for the fabrication of ultra-wideband cavity-backed substrate integrated waveguide antennas on textile substrates is proposed. The antenna cavity is constructed using a single laser-cut electrotextile patch, which is folded around the substrate. Electrotextile slabs protruding from the laser-cut patch are then vertically folded and glued to form the antenna cavity instead of rigid metal tubelets to implement the vertical cavity walls. This approach drastically improves mechanical flexibility, decreases the antenna weight to slightly more than 1 g and significantly reduces alignment errors. As a proof of concept, a cavity-backed substrate integrated waveguide antenna is designed and realized for ultra-wideband operation in the [5.15–5.85] GHz band. Antenna performance is validated in free space as well as in two on body measurement scenarios. Furthermore, the antenna’s figures of merit are characterized when the prototype is bent at different curvature radii, as commonly encountered during deployment on the human body. Also the effect of humidity content on antenna performance is studied. In all scenarios, the realized antenna covers the entire operating frequency band, meanwhile retaining a stable radiation pattern with a broadside gain above 5 dBi, and a radiation efficiency of at least 70%.
Received signal strength indication (RSSI)-based localization is emerging in wireless sensor networks (WSNs). Localization algorithms need to include the physical and hardware limitations of RSSI measurements in order to give more accurate results in dynamic real-life indoor environments. In this study, we use the Interdisciplinary Institute for Broadband Technology real-life test bed and present an automated method to optimize and calibrate the experimental data before offering them to a positioning engine. In a preprocessing localization step, we introduce a new method to provide bounds for the range, thereby further improving the accuracy of our simple and fast 2D localization algorithm based on corrected distance circles. A maximum likelihood algorithm with a mean square error cost function has a higher position error median than our algorithm. Our experiments further show that the complete proposed algorithm eliminates outliers and avoids any manual calibration procedure.
The measurements confirm that MIMO techniques drastically improve the reliability of the wireless link. Measurements are compared for three test persons of significantly different sizes. For equal transmitted power levels, the bit error rates for the 2×2 and 4 × 4 links are much lower than for a system without diversity, with the 4 × 4 system clearly providing the best performance.
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