Abstract
In the 2.45GHz band, indoor wireless off-body data communication by a moving person can be problematic due to time-variant signal fading and the consequent variation in channel parameters. Off-body communication specifically suffers from the combined effects of fading, shadowing, and path loss due to time-variant multipath propagation in combination with shadowing by the human body. Measurements are performed to analyze the autocorrelation, coherence time, and power spectral density for a person equipped with a wearable receive system moving at different speeds for different configurations and antenna positions. Diversity reception with multiple textile antennas integrated in the clothing provides a means of improving the reliability of the link. For the dynamic channel estimation, a scheme using hard decision feedback after MRC with adaptive low-pass filtering is demonstrated to be successful in providing robust data detection for long data bursts, in the presence of dramatic channel variation.
Highlights
The safety of rescue workers can be improved by smart textiles that allow a data communication system to be integrated into their garment
Off-body communication suffers from the combined effects of fading, shadowing, and path loss due to time-variant multipath propagation in combination with shadowing by the human body
Measurements are performed to analyze the autocorrelation, coherence time, and power spectral density for a person equipped with a wearable receive system moving at different speeds for different configurations and antenna positions
Summary
The safety of rescue workers can be improved by smart textiles that allow a data communication system to be integrated into their garment. Measurements were performed deploying two textile antenna patches integrated in a garment on the human body, using short data bursts and treating the channel as time-invariant. Long data bursts containing one million data symbols and lasting over one second are transmitted During this transmission time, the channel is definitely not invariant when communicating with a walking person; a robust system of dynamic channel tracking is needed. Recent work on robust estimation of timevarying channels using various methods to adapt equalizers or filters was presented in [16,17,18,19,20,21,22] These theoretical contributions are very valuable, but their aim is different from the goal of this paper: to investigate the performance of a robust tracking algorithm in an actual measurement scenario, involving a time-variant channel observed over a time period much longer than the channel coherence time. The advantages of using decision-oriented feedback after MRC are illustrated
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