Amplify-and-forward cooperative diversity for green UWB-based WBSNs.

This paper proposes a novel green cooperative diversity technique based on suboptimal template-based ultra-wideband (UWB) wireless body sensor networks (WBSNs) using amplify-and-forward (AF) relays. In addition, it analyzes the bit-error-rate (BER) performance of the proposed nodes. The analysis is based on the moment-generating function (MGF) of the total signal-to-noise ratio (SNR) at the destination. It also provides an approximate value for the total SNR. The analysis studies the performance of equally correlated binary pulse position modulation (EC-BPPM) assuming the sinusoidal and square suboptimal template pulses. Numerical results are provided for the performance evaluation of optimal and suboptimal template-based nodes with and without relay cooperation. Results show that one relay node provides ~23 dB performance enhancement at 1e - 3 BER, which mitigates the effect of the nondesirable non-line-of-sight (NLOS) links in WBSNs.

Toward a highly accurate ambulatory system for clinical gait analysis via UWB radios.

In this paper, we propose and investigate a low-cost and low-complexity wireless ambulatory human locomotion tracking system that provides a high ranging accuracy (intersensor distance) suitable for the assessment of clinical gait analysis using wearable ultra wideband (UWB) transceivers. The system design and transceiver performance are presented in additive-white-gaussian noise and realistic channels, using industry accepted channel models for body area networks. The proposed system is theoretically capable of providing a ranging accuracy of 0.11 cm error at distances equivalent to interarker distances, at an 18 dB SNR in realistic on-body UWB channels. Based on real measurements, it provides the target ranging accuracy at an SNR = 20 dB. The achievable accuracy is ten times better than the accuracy reported in the literature for the intermarker-distance measurement. This makes it suitable for use in clinical gait analysis, and for the characterization and assessment of unstable mobility diseases, such as Parkinson's disease.